Media choice and political participation

Transcription

1 Media choice and political participation The role of media content preferences and media environments in explaining political participation in Europe Alexander, F. Boerboom, BSc Supervisors: Prof. dr. Peer Scheepers Dr. Paul Hendriks Vettehen Master thesis Research Master Social and Cultural Science Radboud Universiteit Nijmegen Nijmegen, August 2015

2 Media choice and political participation The role of media content preferences and media environments in explaining political participation in Europe Master thesis Alexander, F. Boerboom Supervisors: Prof. dr. Peer Scheepers Dr. Paul Hendriks Vettehen Research Master Social and Cultural Science Radboud Universiteit Nijmegen, August 2015

3 Abstract Within European countries overall levels of political participation have been relatively stable in the past two decades. At the same time communication technology has expanded tremendously, and with it, the transmission and accessibility of information, including political information. An explanation for this seemingly paradoxical situation, as proposed by Prior (2005), is rooted in individuals media content preferences. In this study the influences of individual political media content preferences and media environments on political participation were analyzed across 25 European countries and a total of respondents. Multilevel regression analysis was applied to estimate the individual-level effect of political media content preferences and country-level effects of media environment characteristics on political participation. The results showed in general that preferences for political media contents relate positively to all modes of political participation. The country-level influence of the media environment was less clear. Two characteristics of media environments were analyzed: the absolute supply of information and the relative share of political information within this absolute amount of information. Regarding the absolute supply of information by media environments, the regression results were mixed. As expected, the absolute supply of information (indicated by broadband internet penetration rates) widened the voting gap between people with a preference for entertainment and people with a preference for political media content. On the contrary, the unconventional political participation gap between people with different media content preferences closed with increasing broadband internet penetration rates. Moreover, broadband internet penetration rates were positively related to voting and unconventional participation, above and beyond the effects of individual content preferences and internet access. Regarding the relative political information supply by media environments, unexpected but weak empirical evidence was found. The relative supply of political information increased the voting gap between people with different media content preferences.

4 Acknowledgements I would like to express my gratitude to my supervisors Paul Hendriks Vettehen and Peer Scheepers who were very generous with their time and provided me with useful comments and remarks throughout the learning process of this master thesis. The excellent combination of Paul s theoretical knowledge and experience in the field of communication science and Peer s methodological expertise and experience with cross-national research, have made the writing of this master thesis an educational and pleasant experience. Next, I would like to thank the students union den Geitenwollen soc. for the relaxing environment and liters of coffee I consumed there during my writing breaks, but also for all the fun informal activities and social events that made my time as a student very enjoyable. Furthermore, I wish to express my gratitude to my dear friend Ashley, for helping me collecting my data in Amsterdam and to my gym buddy Kirsten for pushing me to stay in physical shape after long days of mental labor. Last but certainly not least, I would like to thank my parents Henk en Karin for their love and support throughout the entire process and for always believing in me.

5 Table of contents Chapter 1 Introduction Introduction Research questions 8 Chapter 2 Theories and hypotheses Conceptualizations of political participation Individual-level explanations of political participation Social and psychological determinants Media content preferences and political participation Contextual-level determinants political participation Scarce empirical evidence Contextual-level effect of the media environment Cross-level interaction effects Empirical evidence Cross-level interaction effect of the media environment 22 Chapter 3 Data and measurements Individual-level data Sampling Response rates and representativeness Data selection and operations Contextual-level data Measurements of Dependent variables Independent variables: relative media content preferences a Relative Entertainment Preference (REP) b Relative Political Content Preference (RPCP) c Media-specific Relative Political Content Preference Contextual characteristics a Media choice within media environments b Absolute information supply by media environments c Relative political information supply by media environments Control variables Missing data 38

6 Chapter 4 Analyses and results Research methods Results Relative political content preferences and political participation Media-specific content preferences Controlling for individuals backgrounds The influence of political interest Political participation across different media environments Cross-level interaction effects of the media environment a RPCP and absolute content availability b RPCP and relative political media content availability Summary of the results Additional analyses Relative media content preferences and political participation Controlling for individuals backgrounds Political participation across different media environments Relative political content preferences and absolute media content availability Relative political content preferences and relative political content availability Summary of the results 71 Chapter 5 Conclusion 73 Chapter 6 Discussion 81 A: Descriptive statistics and full regression tables 85 Appendix B: Additional models 97 Appendix C: Regression models with quasi-metric media content preference measures 100 References 108 Notes 111

7 Chapter 1 Introduction 1.1 Introduction Over the past decades, there has been tremendous progress in mass communication technology. Until the nineties of the previous century, people depended on television, radio and newspapers for most of their (political) information and entertainment. Since the introduction of the internet in the 1980 and its rapid growth since the 1990s, people s access to any information has increased enormously. Nowadays, in most Western countries the internet penetration rates are somewhere between 80 and 100 per cent 1. With the recent introduction of the Smartphone and 3G+ networks that allow people to connect to the internet anywhere at any time, people have more access to information than ever before. The fast developing communication technology and the emerging new forms of communication have intrigued many scholars. Especially their effects on political engagement have been a popular research topic in the field of political communication. New communication technologies have changed the way people gather news and participate in politics (Tolbert & McNeal, 2003). It is increasingly acknowledged that media play a central role in affecting political participatory behavior (Bakker & de Vreese, 2011). According to Delli Carpini (2004), the media are one of the socializing agents that provide much of the raw material that make up social and political beliefs and attitudes. The rise of new media with the fast developing communication technology increased the availability of political information tremendously. One of the scholars that addressed the impact of new media on the political knowledge and participation of citizens is Prior (2005). Prior (2005) noticed that despite of the increases in available political information as a result of progress in mass communication technology (cable television and the internet), political knowledge and participation remained relatively stable in the American society. In order to explain this seemingly paradoxical finding, he developed a theory of how expansions of choice in the media environment affected political knowledge and participation of different segments of the electorate. Cable television and especially the internet have increased the media choice so much that Americans live in a high-choice media environment. This increase in choice has enhanced people s ability to merely expose themselves to the media content they prefer. Politically interested people are more likely to expose themselves to political information and increase their political knowledge, while people who are politically less interested are more likely to avoid political contents and become less politically knowledgeable. Thus, the increased media choice in American society, has widened the knowledge gap between people who are and people who are not politically interested. According to 1 Percentages were retrieved from: 7

8 Prior (2005) these opposite trends in political knowledge levels for people with different content preferences, explain why on average political knowledge levels have remained stable within the American society. Prior (2005) also argued that political knowledge is a strong predictor of turnout and that exposure to political information motivates turnout. Therefore, the increases in media choice are also likely to have contributed to a political participation divide between people with different media content preferences. With the increasing media choice, politically interested people who preferred political media content, gathered more political information, became more politically knowledgeable and were consequently more likely to vote, than people who were not politically interested. Prior s (2005) analyses supported the hypothesis that the relations between content preferences and political knowledge and participation are stronger when media choice increases. Both cable television access and internet access increased the gaps in knowledge and turnout between people who preferred news and people who preferred entertainment. Analyses of Prior s media choice theory with more recent data produced slightly different results. Rittenberg et al. (2012) analyzed more recent waves of the data used by Prior and found little effect of access to internet and cable television on the association between relative entertainment preferences and voter turnout at more recent presidential elections. These findings suggested that Prior s claims of how an increased media choice strengthens the negative association between a relative preference for entertainment and political participation, is not supported in all contexts. Both studies were limited to an American context. The extent to which media preferences and media choice are related political knowledge and participation in countries outside the United States, has not yet been investigated. 1.2 Research questions The media landscape is constantly evolving and the question to what extent new media technology and the increasing media choice in society affect citizens (political) behavior, remains relevant. The studies by Prior (2005) and Rittenberg et al. (2012) were solely based on American survey data, which strongly limits the external validity of their results. To the best of my knowledge, the effect of media choice has not yet been tested within other countries. Most western European countries show similar rates of progress in mass communication technology as the United States (ITU, 2015). A recent analysis of political participation in Europe (Linssen et al. 2014a) showed that, similarly to the United States, political participation within European countries has been relatively stable over time, although there are strong differences across societies. This means that European countries show the same seemingly paradoxical situation as Prior (2005) observed in the United States: mass 8

9 communication technology on the one hand is expanding while political participation on the other hand remains relatively stable. It is therefore relevant to test the assumptions of Prior s Media Choice Theory in the European context. In this contribution the role of individual s media content preferences and the media environment in explaining political participation is investigated, using data on 25 European countries from the European Social Survey (ESS) The ESS(2010) data are much different from the data Prior (2005) used and enabled explicit testing of several of Prior s implicit assumptions. Both the data and the type of analyses that was conducted might contribute to Prior s work in different ways. Prior only tested his assumptions for the American society. By using data from the European continent, the generalisability of his findings to other contexts is tested. Secondly, the ESS(2010) data enabled an alternative approach to the measurement of relative entertainment preference (REP). Whereas Prior (2005) used a single REP measure and implicitly assumed that people have the same content preferences for every media type, the ESS(2010) data distinguished between content exposure by different media types. In this research the relationships between media-specific content preferences and political participation are explored. Moreover, other relevant determinants of political participation are considered in this research next to media content preferences. The first research question reads: RQ1: To what extent are there relationships between people s preferences for political content for different types of media and political participation in European countries, over and beyond other relevant determinants? Another advantage of the ESS data, is that they included multiple countries and thereby allow for the analysis of contextual-level influences of the media-environment, regardless of individual s characteristics. To my best knowledge this approach has not yet been applied and might throw light on the question: RQ2: To what extent are there relationships between media environments in European countries and political participation within these countries? Central to Prior s (2005) work is the hypothesis that when the media choice within a media environment increases, people will increasingly be able to harmonize the media content they are exposed to with their preferences. As a result of these increases in media choice, the relations between individual preferences and political knowledge and participation will strengthen. Prior measured this influence of media choice within the media environment with individual-level access to cable TV and internet. Because the ESS data include multiple countries, I will be able to approach the media environment in a slightly different way. Instead of focusing on individual-level media 9

10 access, I will test for the influence of country-level aspects of available media choice and, moreover, test if there is an environmental effect on the relationship between preferences for political content and political participation, independently of individual-level access. The final research question reads: RQ3: To what extent do the relations between preferences for political content and political participation, vary over European countries with different levels of media choice? 10

11 Chapter 2 Theories and hypotheses 2.1 Conceptualizations of political participation Political participation of citizens is considered a pivotal element for the functioning of healthy democracies (Bakker & de Vreese, 2011). When people participate in politics, they have a voice in public affairs and are able to hold authorities accountable (Verba et al., 1995). Those who do not participate, risk being ignored when policies are made. When the interests of certain people are not considered, inequality in the political process arises. This is in contradiction with the very core of the democratic ideal that all citizens receive equal consideration in the political process (Marien et al., 2010). The concept of political participation has substantially evolved over the past decades. Over time, researchers have proposed several scales and subcategories of political participation. In general, modes of political participation are means for people to voice their needs, concerns and problems to their government (Brady, 1993). With these actions, citizens aim to influence either directly or indirectly the political choices at various levels of the political system. Through their participation, citizens are able to communicate information about their preferences and needs to public officials and pressure them to respond. According to Brady (1993), at the heart of most definitions of political participation, are four basic elements: activities or actions, politics, ordinary citizens and influence. A classic description by Verba and Nie (1967), that incorporates these elements reads: those activities by private citizens that are more or less directly aimed at influencing the selection of governmental personnel and/or the actions they take. Most definitions of political participation usually include these four elements and do not deviate much from the classic formulation (Brady, 1993). The versatile nature of the concept of political participation has resulted in a wide range of operationalisations in past research. Early research merely focused on voting and campaign activities. These are solely activities that are part of the electoral process. In later research it was emphasized that next to these traditional or conventional channels of participation, there were other ways through which citizens could attempt to influence governmental action. Political protesting, signing petitions, participating in demonstrations or even violent actions could be considered as political participation as well. In first instance, these forms of political action were classified as unconventional political participation (Barnes & Kaase, 1979). Participants in this form of political action try to influence the decision making process in a political system from outside the system. The division of conventional and unconventional political participation (although sometimes labeled differently) became the standard in research and is still widely used today. Labeling political participation as either conventional or unconventional is misleading, according to Marien et al. (2010). Many political activities that were previously classified as 11

12 unconventional have become more generally accepted and performed in society. According to these scholars it is therefore more accurate to classify political activities as being institutionalized or non-institutionalized. Political activities at which participants try to influence decision making from within the political system, are considered institutionalized. The non-institutionalized activities are not part of the system and include those activities that take place outside of the political arena which are aimed at influencing political decision making. The latter activities are becoming more prevalent in most liberal democracies while institutionalized forms of political participation such as voter turnout and party membership are in decline (Marien et al., 2010). These claims do not hold for Europe according to two recent studies on determinants of, and trends in political participation (Linssen et al., 2014a; Linssen et al., 2014b). In these studies, similar patterns for conventional and unconventional participation were observed. Both forms of participation have remained relatively stable after the turn of the millennium. The results did not show any mass withdrawal from conventional channels, nor a replacement of conventional with unconventional means of participation. With regard to the individual- and contextual-level determinants of both forms of participation, similarities were found as well. Socio-demographic characteristics and contextual mechanisms that govern conventional and unconventional participation are relatively similar (Linssen et al. 2014b). Nevertheless the scholars did note that: conventional and unconventional political participation are qualitatively different phenomena. Because both forms of participation are still considered qualitatively different, both conventional and unconventional participation are taken into account in this research and are analyzed separately. Explaining differences between both types of participation is beyond the theoretical scope of this research. Therefore differences between both types were not taken into account when formulating the hypotheses. Nevertheless, different modes of political participation were analyzed separately, because both forms are considered qualitatively different. 12

13 2.2 Individual-level explanations of political participation Social and psychological determinants It has often been demonstrated that political participation in western democracies is strongly associated with socio-economic and demographic background characteristics of citizens. The level of education, social class, age and gender of citizens have often found to be correlated to their likelihood to participate in politics (Brady et al. 1995, Marien et al. 2010, Stolle & Hooghe, 2011), both conventionally and unconventionally (Barnes & Kaase, 1979). This inequality in participation among different groups of socio-economic status suggests that not all people are equally represented in the political process and emphasizes the importance of understanding the underlying mechanisms that induce these inequalities. Why certain socio-economic categories of people are more likely to participate in politics than others has often been ascribed to psychological and attitudinal factors as political knowledge, interest and efficacy (Brady et al. 1995; Barnes & Kaase, 1979; Tolbert & McNeal, 2003). Political knowledge is essential to know where, how and whom to vote for. According to Verba et al. (1995) there is a political knowledge gap between socially advantaged and disadvantaged people. Because socially disadvantaged people are on average less informed about politics, they feel more alienated from the political system and refrain from participation. Political efficacy is considered a sociopsychological precondition of political action (Barnes & Kaase, 1979). It is the belief of citizens that they can understand and influence political affairs. Political interest is especially a strong predictor of voter turnout (Brady et al., 1995). A drawback of these measures of psychological engagement with politics is that they are very close to the activity itself. They are statistically strong predictors of political participation, but the theoretical relevance is not clear. Being politically interested is a precondition of engaging in politics. According to Brady et al. (1995), it is theoretically more meaningful and methodologically more reliable to explain political participation from a resource perspective. These scholars developed a resource model to explain the inequalities in political participation among different social categories. According to this model there is an unequal distribution of resources among people with different levels of education and income, underlying the inequalities in political participation. These resources are money, time and civic skills and are considered essential requisites for participation. The level of social stratification varies for these different resources. Money for instance, is more strongly related to socioeconomic status than time. Furthermore these different resources were found to relate differently to various types of political participation. Civic skills, for example, were associated with political acts requiring an investment of time like working in a campaign or taking part in a protest. Money was found to affect those political acts that involved an investment of 13

14 money, such as contributions to campaigns. Political participation has often been found to be strongly related to socio-economic and demographic background characteristics like education, social class, age and gender. Explanations for these associations have traditionally been ascribed to psychological and attitudinal factors and unequal distributions of resources. The focus of this study, however, is not on social and psychological determinants of political participation but on influences of media content preferences and media environments. Socio-economic and demographic background characteristics are included in the analyses to control for possible spuriousness among the relationships and avoid omitted variable bias Media content preferences and political participation Next to the traditional explanations that emphasize the importance of demographic, socio-economic and psychological determinants of political participation, there is a strand of literature that particularly focuses on the influence of mass communication technology. Empirical evidence from this body of research indicates that changes in communication technology are associated with changes in political participation. Sources of mass communication provide people with political information that influences their political knowledge and behavior. Changes in technology have changed the way many people gather news and participate in politics (Tolbert & McNeal, 2003). For a long time, the focus in this tradition of research has been on the influence of media sources such as radio, television and newspapers. With regard to these traditional media sources, the empirical evidence was mixed. Some studies indicated positive effects of newspaper reading on political knowledge and participation (Scheufele & Nisbet, 2002; Bakker & de Vreese, 2012), while others have claimed that voter turnout is not affected by newspaper reading (Gerber et al., 2007). Research on the effects of radio on political knowledge and behavior is very limited. Strömberg (2004) analyzed data on radio exposure in America from the period and showed that radio in this period positively affected voter turnout. Hoffstetter et al. (1999) showed that active listening to radio corresponded to higher levels of political knowledge, with the exception of conservative talk radio which increased the likelihood of being misinformed. Television, which received most attention in research, has often been negatively associated with political knowledge and behavior. According to Putnam (2000), television has individualized leisure time which eroded social interaction and active civil engagement. Gentzkow (2006) observed a negative association of television viewing with voter turnout in the United States. Prior (2005), on the other hand, claimed that television provides political information which has the ability to teach people about politics and increase their involvement in the political process. He emphasized the importance of taking the content that people are exposed to into account. Sheer exposure to a 14

15 medium is not informative about the transmission of political information. Exposure to political content increases political knowledge, while exposure to entertainment does not. Bakker & de Vreese (2011) indicated that news consumption through television was positively related to traditional and digital political participation. Rittenberg et al. (2012) took it a step further and distinguished between different types of news. Especially the exposure to public affairs news had a strong influence on voter turnout. These positive effects of television news, however, do not apply to everybody, since not everyone is equally exposed to news and political content. Those in charge of the remote control, decide over the amount of exposure to political information. People who prefer entertainment over political content, may tune out of politics completely and become less politically knowledgeable and less likely to vote. Thus, television can either have positive or negative effects on political knowledge and behavior depending on people s content preferences and levels of political interest. This versatility of television and other mass media sources is increasingly acknowledged in research. The need to discriminate between exposure to different types of content is well established today and explains why previous research has led to inconclusive results (Bakker & De Vreese, 2011; Rittenberg et al. 2012; Shah et al., 2001). During the last decade, the focus in research has shifted to the effects of the latest revolution in mass communication technology: the internet. Within thirty years after its introduction to the public, the internet has acquired a central place in society. Access to the internet has extended our informational and interactive capabilities. It has provided people with a massive information resource and a vehicle of social interaction (Papacharissi, 2002). In comparison to traditional media, the interactive nature of internet has given users much more control over the content they are exposed to. Content exposure is far more selective and based on users preferences. Because the internet is such an important source of information and means of interaction for many people nowadays, the question to what extent it influences their political knowledge and behavior has gained much academic attention. Some scholars are optimistic about the potential of the internet to increase political efficacy, knowledge and participation, while others argue that the internet has a negative impact (Bakker & de Vreese, 2011; Kenski & Stroud, 2010; Tolbert & McNeal, 2003; Scheufele and Nisbet, 2002). Scheufele and Nisbet (2002) found that the internet plays a very minimal role in promoting active and informed citizenship. Tolbert and McNeal (2003), on the other hand, claimed that internet exposure to election news during the presidential elections in the US in 1996 and 2000 increased people s voting probability. Other studies have also indicated positive effects of the internet on political participation (Kenski & Stroud, 2010; Bakker & de Vreese, 2011). Bakker & de Vreese (2011) argued that the medium offers people alternative and digital ways of participation. It offers many 15

16 political engagement opportunities like visiting political blogs, political websites, following online news or participating in forums. They indicated an influence of internet use on digital and traditional forms of political participation among the youth. As is the case with television exposure, the internet does not affect everyone in society equally. Among internet users much inequality exists in user patterns, which are associated with individual s interests. People who access political information via the internet are likely those who were already interested in politics (Xenos & Moy, 2007; Bimber, 2003). According to Prior (2005) this is creating a political knowledge and participation gap between politically interested and politically uninterested people. He found that media influence people s political knowledge and participation and that this influence depends on how people use these media. Prior developed a media choice theory around this relation. Starting from a simple dichotomy in media choice between the two broad genres news versus entertainment, he assumed that people constantly have to choose between news or entertainment when they use media. People with a preference for political content will consume news which includes political content and increases their political knowledge. People with a preference for entertainment on the other hand will merely consume entertainment and will not increase their political knowledge. The gap in political knowledge that occurs between people with different preferences is what in turn causes the gap in their political participation. Prior expressed the preference for either entertainment or politics in a measure he referred to as Relative Entertainment Preference (REP). It is a relative measure because a high preference for entertainment goes at the expense of political preferences. Derived from these assumptions is the first hypothesis: H1a: The higher peoples relative preference for political media content, the more likely they are to engage in political participation. Prior s (2005) analyses revealed an implicit assumption which he did not substantiate. He created a single REP measure and interacted this with cable TV and internet access. By doing so he tested whether the relation between preferences and political knowledge and participation, was different for people with and people without access to these media. However, underlying these interaction effects is the assumption that people have a preference for politics or entertainment independent from the type of media they use. Whether it is a radio, newspaper or the internet people are using, people are assumed to have a constant level of preference for political content. The ESS(2010) data that is used in this research, distinguished between media-specific preferences. This enables the testing of the implicit assumption that the relative preference for entertainment or politics is the same for all media types. Although there is theoretically no strong reason to believe that the implicit assumption is false, it could well be the case that people have different preferences for different media types. When people have read a newspaper in the morning, 16

17 they might not spend much time on reading web news if their need for political information has already been satisfied. In other words, people might have media-specific content preferences and these might be related to each other. How media-specific preferences would affect each other is not clear. They might either replace or reinforce each other. Therefore I will only test the assumption by Prior (2005) that content preferences do not differ across different media types by proposing the more specific hypothesis: H1b: The associations between relative media content preferences and political participation vary across media types. 17

18 2.3 Contextual-level determinants political participation Scarce empirical evidence The literature on political participation contains very few cross-national multi-level studies. Therefore contextual effects have not been considered much. Next to the effects of individual s backgrounds or psychological engagement with politics, citizen s propensity to vote or engage in other political activities might be affected by their environments. Linssen et al. (2014b) argued that individual characteristics such as education, class and deprivation cannot fully explain the large cross-national differences in political participation in Europe; cross-national differences that have been shown to be rather stable over time within countries since the turn of the century. Variance in political participation across these different countries might therefore be induced by factors that are specific to these countries. Jackman (1987) explained country differences in political participation by the difficulty of countries voting systems. In some countries voting is more difficult and less rewarding than in other countries. In a recent cross-national study on political participation in European countries (Linssen et al., 2014b), the importance of several other country characteristics was emphasized. The political openness of a country was positively associated with conventional forms of political participation (membership and working for political parties). Furthermore it was found that countries prosperity induced unconventional political participation. People in more prosperous countries were also more likely to work for or be members of political parties. However, no effect of prosperity on voting was found. Another minor but significant effect was indicated for countries social security systems. Countries with more elaborate social security systems had higher rates of unconventional political participation. Previous research has not yet accounted for contextual-level effects of the media environment when explaining political participation. If individual media use influences political knowledge and participation (Prior, 2005) it seems plausible that differences in media environments also play a role Contextual-level effect of the media environment Prior (2005) proposed contextual-level media environment effects but could not account for these effects because he used single country data. To account for the technological developments within the media environment, he compared people with and without individual access to cable television and broadband internet. In his theoretical framework he proposed that developments in mass communication technology within media environments increase the availability of information and contents people can choose from, including political information. This in turn should increase the political knowledge and participation of citizens. Prior (2005) noticed however, that despite of the developments in mass communication technology, political participation did not increase in America. He explained this stable political participation in the American society during a time of fast 18

19 developing mass communication technology by the concepts of media preferences and media choice. The increases in the supply of information that go hand in hand with the developments in the media environment, provide people with a higher amount of choice. This increased media choice has different effects on different groups of people, Prior claimed. The group of people with a high preference for political content will increasingly choose political content and increase their political knowledge and participation. People with a low preference for politics will focus their attention on the entertainment contents media have to offer and will not increase their political knowledge or participation. Even a negative effect of media choice on the political participation of these people can be expected due to the declining incidental news exposure. When people are better able to avoid political content due to increases in media choice, incidental political content exposure diminishes. Thus, what Prior argued, in short, is that there are two groups of people (low and high political preference) whose political participation is affected differently (negatively and positively) by media choice. Prior did not account for direct effects of the media environment on political participation. The extent to which increases in media choice (through the introduction of new media), affected political participation independently of media content preferences was not substantiated. Prior initially introduced relative media content preferences (news versus entertainment) to explain the seemingly unrelated trends of increasing political information availability on the one hand and stable political knowledge levels on the other hand. He stated that: Distinguishing between people who like news and take advantage of additional information and people who prefer other media content explains a puzzling empirical finding: despite the spectacular rise in available political information, mean levels of political knowledge in the population have essentially remained constant. (Prior, 2005, p ) People who like news, take advantage of additional information and become politically more knowledgeable he claimed. People who prefer entertainment over news will not take advantage of the additional information. Additional information therefore creates a political knowledge gap between people with different content preferences. The above statement implies that when the two groups with different media content preferences (which relate to political knowledge differently) are taken together, the opposing effects level each other out and show a stable political knowledge 19

20 trend. 2 Following Prior s reasoning, if the contextual-level concept of information supply is isolated and not interacted with individual-level political content preferences, it can be expected that: H2a: The absolute amount of information that is provided within media environments, does not affect political participation. Prior (2005) concluded that increases in media choice through technological development, increase the impact of content preferences on users choices, and make them key to understanding the political implications of new media. These increases in media choice have only been assumed and not quantified. In his analyses Prior compared users and non-users of cable television and the internet and assumed that these media offer more choice. Although these assumptions are plausible and the results indeed showed that having access to new media widened the gap between people with different preferences, the increase in media choice is still assumed and not quantified. It would be interesting to know the volume and nature of the contents that new media offer, i.e. the supply side of the media environment. Until now, research did not pay attention to this aspect of media choice. Media choice has only been approached from individuals point of view and operationalised by individuals access to new media. The use of multilevel data in this study, enables the estimation of media supply by media environments, independent from individual-level media access. In this research I propose a new contextual-level measure of relative political information supply by media environments. People constantly have to choose between entertainment or news contents when using media and these media choices relate to political knowledge and participation differently (Prior, 2005). The choice of media users to consume either entertainment or news is inextricably linked to the supply of media content. People can only choose to watch the evening news if their media environment provides them with evening news. Media choice is affected by media supply and therefore a relative supply measure that takes the entertainment/news ratio into account is desirable. Especially in Europe, where since the 1980s television broadcasting shifted from public service domination to a multichannel environment commanded by commercial providers. With the introduction of cable television in Europe, commercial television flourished. The contents provided by commercial television channels were strongly focused on entertainment (Wieten et al., 2000). This means that while the total supply of media contents increased (more television channels) in Europe, the entertainment/news ratio probably shifted towards less news and more entertainment. It seems that for television in Europe, the total supply of media content and the 2 By assuming that stable levels of political participation over time actually hide two diverging trends for different preference groups, Prior implicitly assumed stable relationships between the sizes of both groups and between the strengths of their associations with political knowledge. 20

21 relative supply of political information are negatively associated. In this study both the absolute and relative supplies of media content are taken into account to test their relations to political participation in Europe simultaneously. With respect to the relative supply of political media contents the hypothesis is that: H2b: The relative amount of political information that is supplied within media environments positively affects political participation. 21

22 2.4 Cross-level interaction effects Empirical evidence Previous research indicated that effects of individual-level characteristics on voting, differ across national contexts. Gallego (2010) showed that in many European democracies, there was little to no effect of education and income on voter turnout. This is contradictory to most empirical evidence from the United States, where a positive correlation between these characteristics and voter turnout has often been found (Barnes & Kaase, 1979; Brady et al. 1995). These between-country differences in the extent to which education and income affect voter turnout, suggest that the effects of individual characteristics on turnout rates are to some extent dependent on context-specific factors. Previous research on cross-national differences in political participation has identified several contextual characteristics that foster inequality in political participation between groups of different social status. A study by Anduiza (2002) provided evidence that when voting becomes more cognitively challenging, for example when citizens are confronted with more choices, people with less resources and motivation are less likely to vote. The number of political parties in elections was found to positively affect the relation between resources and political participation. Contextual-level media effects have only been predicted, but not tested for in previous research. Prior (2005) proposed different effects of the media environment on the political knowledge and participation likelihoods of people with different media content preferences. His use of individual-level data has left the question unanswered to what extent the relationships between different media content preferences and political participation vary across different media environments Cross-level interaction effect of the media environment Prior (2005) argued that with developments in mass communication technology, the provision of information within media environments increases. As a consequence media users have more media choice and are better able to expose themselves to the contents they prefer. People who prefer political content will tune in to politics and people who prefer entertainment will avoid the news. A political knowledge and participation gap between people with different preferences results from an increasing media choice. Therefore the first interaction hypothesis reads: H3a. The absolute amount of information that is provided within media environments, strengthens the positive relations between relative political content preferences and political participation. 22

23 In a previous section (2.3.2) it was argued that media choice is a relative concept that depends on the availability of media contents. If a higher share of the total available media content is considered political, people with a preference for political media content are better able to consume these contents. They are likely to increase their political knowledge and participation by consuming more political media contents. Another result from a higher share of political media content might be that people with a preference for entertainment over politics, are less able to avoid political content. It is likely that their accidental exposure to political content will increase which increases their political knowledge and their likelihood to participate politically. Higher relative amounts of political information within media environments can therefore be expected to close the political knowledge and participation gap between people with different content preferences. H3b. The relative amount of political information within media environments, weakens the positive relations between relative political content preferences and political participation. 23

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25 Chapter 3 Data and measurements 3.1 Individual-level data In order to test the hypotheses formulated in the previous chapter, data from the European Social Surveys (ESS) were used. These are cross-national surveys that monitor social change across Europe and have been conducted every two years since The surveys cover the attitudes, beliefs and behavior patterns of diverse populations in over thirty European nations. Between 2002 and today, six waves of the ESS have been published. Taken together these different waves provided data for 36 European countries. For this thesis I used the fifth wave, because this was the most recent ESS wave including information on respondents internet use. The fieldwork for the fifth wave was targeted between September and December This target was not achieved and the fieldwork was gathered in the period between September 2010 and August Sampling The 2010 ESS wave included 27 European countries. The population consisted of all people in the residential population of each country aged 15 years or older, regardless of nationality, citizenship or legal status, that were selected randomly. Countries with a population of two million residents were required to achieve an effective sample size of minimal 1500 completed interviews. Countries with less than 2 million inhabitants had to achieve a sample size of 800 respondents. The data were collected by face-to-face interviews, between September and December in Response rates and representativeness A response rate of 70 percent per country was targeted in the 2010 Survey. In order to achieve these high response rates, several measures were used, such as advance letters to respondents, multiple attempts of contacting each potential respondent and the use of incentives. Various kinds of conditional and unconditional incentives were awarded in a monetary or non-monetary (minicomputer lottery participation) form (ESS, 2010b). Despite of the many efforts to maximize response rates, the 70% target was only achieved for five out of the 27 countries. The average of countries actual response rates was 60.18% 3. The survey was aimed to be representative of all people in the residential population of each country aged 15 years or older, regardless of nationality, citizenship or legal status. In order to test for the representativeness of the sample, analyses have been conducted in which the sociodemographic sample composition of the ESS data was compared with more accurate external benchmark data from the European Union Labor Force Survey (LFS). These analyses revealed small 3 The percentages were retrieved from 25

26 differences between the ESS and the LFS data for six socio-demographic variables: gender, age, marital status, work status nationality and household size. For some specific countries larger differences were observed (ESS, 2010c). To what extent these sample deviations are problematic for the analysis of ESS data, was not broached in the report Data selection and operations The unprocessed ESS 2010 data set contained respondents from 25 countries 4. These 25 countries are displayed in Table 2. The final sample sizes per country ranged from 975 respondents from Cyprus to 2667 respondents from Germany. Because this study is focused on the effects of content preferences on political participation, respondents with invalid scores on these key variables were excluded. After the replacement and removal of missing values, the final data set comprised respondents from 25 countries. 3.2 Contextual-level data In order to test the hypotheses on the influence of the media environment, the individual-level ESS data were enriched with some country-level characteristics. Several indicators of media availability in European countries were retrieved from the European Audiovisual Observatory (EAO) 5. The European Audiovisual Observatory is part of the Council of Europe and is a public service organization. It collects and distributes information about the audiovisual industries in 40 (mostly) European countries. The Observatory publishes the information in statistical yearbooks, of which the 2010 edition was used for this research. The data presented in this yearbook were gathered in Most countries in the EAO yearbook overlap with the countries included in ESS(2010). The EAO collaborated with several other organizations which provided the data on television markets. These organizations are the European Broadcasting Union (EBU), Screen Digest and Eurodata-TV Worldwide. 3.3 Measurements of Dependent variables The dependent variable political participation was subdivided into conventional and unconventional political participation. Conventional participation entails those activities that are part of the electoral process and unconventional participation on the other hand refers to those 4 Ukraine and Israel were excluded because no contextual-level data were available for these countries. 5 Data are extracted from the European Audiovisual Observatory s 2010 Yearbook of Statistics, which contains European country statistics from

27 activities taking place outside of the electoral process. There are several activities measured in the survey, that can be classified as conventional political participation. Respondents were asked whether they voted in the last national election. Furthermore they were asked whether they were a political party member or worked in a political party or action group, during the last 12 months. Linssen et al. (2014b), who also analyzed conventional political participation activities from ESS data, argued that voting is a distinct activity from party membership or working for a party, because it is only done once every few years. It is a less time consuming form of participation that requires lower commitment. Furthermore, voting is by far the most popular activity. If a single scale would be constructed out of the three activities, voting would disproportionally influence the total scalescores. Inspection of the ESS2010 data supports this finding 6. Similarly to the study by Linssen et al. (2014b) I will use two indicators of conventional political participation. Political party membership and working for a political party or action group are scaled together, and analyzed separately from voting. Descriptive statistics of these measures are presented in tables 1 to 4. Several activities that are considered unconventional participation, were measured in ESS. These activities are signing a petition, taking part in a lawful public demonstration and boycotting certain products. Respondents were asked to answer whether they participated in these activities during the past 12 months with yes or no. Following Linssen et al. (2014b) who provided crossnational evidence for robust scalability and moreover equivalence of these measurements, I combined these three activities to create a single participation measure. If a respondent participated in any of the three unconventional activities, he or she was considered an unconventional political participant. In Table 4 an overview of descriptive statistics of unconventional participation in each European country in the data is presented. 6 76% of the respondents voted in the last national election and only 6% of the respondents was member of, or worked for a political party. 27

28 3.3.2 Independent variables: relative media content preferences As mentioned before in the background section of this thesis, I use measures of relative preferences that are quite different from Prior s (2005) Relative Entertainment Preference (REP) measure. Before I will elaborate my own relative preference measures I will first discuss Prior s original REP measure a Relative Entertainment Preference (REP) According to Prior (2005) television viewers must commit to one particular program and cannot watch two programs at the same time. This means they have to evaluate the different programming options and choose between either news or entertainment. Since they cannot watch both at the same time they have to evaluate the different options relative to each other. Prior asked respondents to select their favorite genre from a list of 10 genres. He then asked the same question for the remaining 9 genres and repeated this procedure twice more. After a ranking of their top four genres was established, respondents were asked to mark all the remaining genres they really disliked. With this information, Prior constructed a six-point scale, measuring peoples relative preference for news over entertainment. Respondents who said they dislike news were coded 5, people who neither disliked nor selected news as their favorite genre were coded 4, respondents who selected news in their top four favorite genres were coded 3,2,1 or 0, depending on how high they ranked news. The higher respondents scored on this REP scale, the more they preferred entertainment over news. The ESS data did not contain any information on respondents favorite television genres. Therefore the reproduction of Prior s REP measure was not possible. However, the ESS data did contain several items on TV, radio and newspaper exposure which were used to create a measure that indicates relative preferences for entertainment or political media content. This measure is called: Relative Political Content Preference (RPCP) and its construction is further elaborated in the next section b Relative Political Content Preference (RPCP) The European Social Survey contained several items on media use that were used to construct the relative preference measures. First, respondents were asked how much time they spent on an average weekday, watching television, listening to the radio, reading a newspaper and surfing the internet. Answer categories ranged from 0 to more than 3 hours, for television, radio and newspaper. For the internet, the questions and answer categories were quite different, but this will be discussed later on. After respondents were asked the amount of time they spent on the use of each media source, they were asked how much of this time was spent on politics and current affairs 28

29 (except for the internet). Again, the answer categories ranged from 0 to more than three hours. Since the ESS included measures of total time spent on different media types and measures of time spent on political content, it was possible to calculate a relative preference for politics. By dividing the amount of time people spent on politics and current affairs by the total time they spent using media, a measure was constructed that will henceforth be referred to as Relative Political Content Preference (RPCP). Prior (2005) assumed that a high preference for entertainment goes at the expense of a preference for politics. The RPCP measure can be interpreted as an inverse REP measure. A high score on REP implies a low score on RPCP and vice versa. Entertainment and politics were assumed to be mutually exclusive, meaning that a high preference for politics infers a low preference for entertainment. In first instance, a single RPCP measure was constructed for all traditional media types (television, radio and newspaper) combined for two reasons. The first reason was to approach Prior (2005) as close as possible, who also used a single REP measure for different media types. The second reason was that there was a high number of missing values on the amount of time that was spent on politics and current affairs. By combining these variables the amount of missing values was strongly reduced. The RPCP measure was calculated in two steps. First, the original ordinal media variables (total and political exposure)were transformed into scale variables, by assigning new scores to the original answer categories. The new scores refer to the amount of hours and are exactly in the middle of the range from the original categories. 7 The transformations were as follows: No time at all = 0; Less than 0,5 hour = 0,25; 0,5 to 1 hour = 0,75; More than 1 hour, up to 1,5 hours = 1,25; More than 1,5 hours, up to 2 hours = 1,75; More than 2 hours, up to 2,5 hours = 2,25; More than 2,5 hours, up to 3 hours = 2,75; More than 3 hours = 3,25. Next, the RPCP measure were constructed as follows: By combining all media sources in a single measure, the number of missing values was reduced to a minimum. Only 833 respondents did not spend any time on news and programs about politics and current affairs on all three media sources combined and were excluded from the analyses. 7 The transformation of the upper category more than three hours was problematic, since its upper boundary was not defined. This category might include respondents watching television for 10 or more hours a day. I chose to assign the value 3,25 to this category to keep a constant 0.5 hours distance between the new categories. 29

30 3.3.2c Media-specific Relative Political Content Preference In contrast to Prior s (2005) data, the ESS data differentiated between content preferences for different media sources. By analyzing the effects of RPCP for television, radio and newspaper separately, Prior s implicit assumption that people only have one preference that can be applied to all media sources, could be tested. By conducting analyses with these separate RPCP measures, It could be researched whether the effect of political preference on political participation was stronger for some media types than it was for others. Scale transformations of the media variables were used to calculate the media-specific RPCP measures. These were constructed as follows: A drawback of using these separate measures is that there was a high amount of respondents with RPCP radio and RPCP newspaper scores of 0. This was because of the high amount of respondents spending no time at all reading newspapers (34%) or listening to the radio (28%). How to deal with these respondents was complicated. It could be argued that people who are not interested in using media at all are automatically not interested in any (political) content these media have to offer. These respondents should have then been assigned the lowest RPCP score (0) possible. However, since the RPCP measure is a relative preference measure, an RPCP score of 0 would imply that the respondents are only interested in entertainment. This is in conflict with the first assumption that non-users are not interested in any media content. Since roughly a third of the respondents do not use newspapers for example, the highest preference for entertainment would be assumed for this vast share of respondents. Another option was to exclude all non-users from the analyses. Although it might theoretically be a better solution, this would reduce the dataset with nearly half of the respondents. A third, and in my opinion better option, was to change the measurement level. I chose this option and used dummy coding to include the RPCP measures as nominal categories in my analyses. The RPCP scale ranging from 0 to 1 was recoded into five categories: 0 = only entertainment; = mostly entertainment; = equal preference; = mostly politics; 1 = only politics. The dummy coding approach enabled me to include a sixth category for all respondents with missing RPCP scores. Therefore no respondents needed to be excluded from the analyses. 30

31 All RPCP variables were transformed into nominal variables. In Table 6 the associations between all RPCP measures are presented. The association between two nominal variables is expressed in a measure called Cramér s V. This measure merely expresses the strength of association between two nominal variables and is no correlation coefficient. Two things are worth mentioning regarding the associations. First, the associations between the different RPCP measures are rather weak (± 0.14), meaning that political preferences for different media are not strongly related. The use of mediaspecific preferences might therefore present a more qualified picture of the relation between political content preferences and political participation. However, these more nuanced measurements might also muddle the general picture of how content preferences and political participation are related. Second, the single overall RPCP measure is strongly associated with the television RPCP measure (± 0.6) and less strongly with the radio and newspaper RPCP measures. This means that the single RPCP construct is strongly influenced by the television component and that RPCP and RPCP television virtually measure the same concept. Table 1 provides an overview with descriptive statistics of the general RPCP and media-specific RPCP measures. Unfortunately, the survey failed to provide insight in internet user patterns. The question of how much time was spent on politics and current affairs was not asked for the internet. The only available information on internet use is the amount of time spent on surfing the internet for personal use. Answer categories to this question differed from the other media variables and consisted of the options: No, access at home or work ; never use ; less than once a month ; once a week ; several times a week ; Every day. Because of the lack of information on internet user patterns this medium was discarded. 31

32 3.3.3 Contextual characteristics Prior s (2005) theory stated that the extent to which respondents political participation is affected by their relative political content preference is influenced by the amount of media choice they have. Advances in mass communication technology in society are associated with an increasing media choice and an increase in the amount of available (political) information. With the introduction of new technologies like the internet, the variety of contents people can choose from increased tremendously. People became increasingly able to select the media content they prefer. Incidental exposure to news if not preferred becomes less likely with the increasing media choice. Also the effect of peoples preferences on their political participation are expected to be moderated by the contextual-level availability of mass communication technology. It is therefore crucial to account for the amount of media choice at the contextual level a Media choice within media environments Prior (2005;2007) argued that changes in the media environment brings about increases in the media choice people have, but did not empirically account for the influence of their (media) environments. Even though the media environment is a central concept in his work - My central claim throughout this book is that the media environment the types of media to which people have access explains many systematic variations in the amount of free information received. (Prior, 2007) - he did not directly test for contextual-level effects. Instead, he used individual-level access to the media environment as an indicator of media choice offered by the environment. By merely looking at the types of media people have access to, the supply side of the media environment is underexposed. Testing for the individual-level effect of having access to the internet, is not informative about the media choice (selectable contents) that the media environment offers. In other words, Prior s analyses were built on the implicit assumption that having access to internet is associated with more media choice. Although this is a reasonable assumption, it remains unclear how much peoples choice increases when having access to the internet. Another drawback of individual-level cable or internet access as a measure for media-choice within media environments, is that it might depend on people s preferences. It is plausible that people subscribe to internet because they would like to gather more (political) information for example. In this case, their internet access or more abstract media choice is a result of their preferences. The concept of the media-environment is then not an exogenous environmental characteristic that influences the relation between preferences and political participation, but rather an endogenous characteristic that is shaped by preferences. In this research contextual-level media availability was used as a measure for media choice within media environments. Endogeneity is less of an issue for the cross-level interaction of country- 32

33 level media availability with the individual-level relation between preferences and political participation. It is unlikely that an individual s preference affects the media availability in his country. Therefore the influence of the media environment, regardless of individuals preferences is better approached in my opinion, with the use of contextual-level characteristics. In this thesis, multilevel analyses were applied and contextual-level characteristics were included as proxies for the media environment. Several country-level characteristics were included in the analyses that indicate countries state of development in mass communication technology and countries relative share of public broadcasting, as a proxy for political information supply by countries media environments. By including these contextual characteristics two different aspects of the theoretical concept of the media environment were captured which will be explained in the next two sections b Absolute information supply by media environments One important aspect of the media environment is the availability of media sources or mass communication technology. Prior (2005; 2007) argued that advances in mass communication technology are associated with increases in the availability of (political) information and the amount of choice that people have to select contents they prefer. By measuring countries state of technological development with the penetration rate of broadband internet, the absolute provision of (political) information was assumed to be captured. Technologically more advanced countries provide presumably more information and higher levels of choice than technologically less advanced countries. In first instance, the idea was to include countries penetration rates of TV and cable TV as proxies for countries states of mass communication technology. Since its introduction halfway the twentieth century, television has evolved a lot and the amounts of information and entertainment it provides have increased tremendously. It seems that the technological improvements of television go hand in hand with increases in information supply. Therefore it seems likely that technologically more advanced countries, have better television technology (cable TV) and offer more media choice (channels and programs). A close inspection of the EAO data revealed that this assumption is too simplistic. There are several highly developed Western European countries with low rates of cable TV penetration. This does not automatically imply that the supply of information and entertainment or media choice in these countries is low. Because of the high costs involved with the installation of cables, people in some of these countries rely on alternatives to cable TV, such as satellite television. Although cable television might be technologically more advanced than satellite TV, they are not that different in terms of media choice. Satellite television offers access to many channels inferring a high media 33

34 choice for its users. Therefore the rates of cable TV penetration were not included in the analyses. It was believed not to be a good or valid indicator of the information supply by the medium television. Instead the total number of television channels (terrestrial + cable + satellite) within countries were retrieved from the EAO data, and included as a measure of absolute information supply. The medium internet is easier to compare across countries. Improvements in internet connectivity are less directly linked to the information supply by the internet. An Individual s connection to the internet does not influence the information the internet offers to this person. The amount of information this individual is able to consume from the internet particularly depends on the information transmitting capacity of his internet connection. If this person was to improve his internet connection, the information availability would not increase, but merely the efficiency of his connection, enabling him to download more information in the same amount of time. It seems more likely that web contents influence the type of internet connection people desire. With the increasing information transmitting ability of internet connections over the years, web contents have also changed drastically. Two decades ago web pages mainly contained texts whereas today Flash, animations and streaming videos for example are standards. These are contents that need fast internet connections in order to be properly displayed. It can therefore be argued that people with better internet connections (in terms of information transmitting capacity), have a higher access to information. At a societal level this infers that the higher the amount of highspeed internet connections, the larger the transmission of information is within this society. Ranking internet connections on the basis of their ability to transmit information is a relatively easy task. The speed of internet connections is indicated by its data signaling rate (DSR) which is usually expressed in bits per second. This rate expresses the amount of data that is transmitted through the internet connection. Whereas in the early days of the internet analog connections (dial-up internet) with limited speed and data transmission were the standard, today analog has been widely replaced by broadband internet. Broadband commonly refers to high-speed internet access that is always on and faster than traditional dial-up access 8. The EAO data provided percentages of households within European countries with broadband connections. These percentages were included in the analyses as a proxy for information availability through the internet, assuming that high percentages of broadband connections within countries indicate a high transmission of information in these countries. I m aware that broadband internet is a general concept that includes several different connection types (e.g. DSL, cable modem, fibre) with varying data transmission rates. In table 5 descriptive statistics of the penetration rates of the internet are presented

35 3.3.3c Relative political information supply by media environments Societal rates of internet penetration alone, might indicate the absolute availability of information, but do not really indicate to what extent societies are high-choice environments. In the theoretical section of this thesis it was proposed to zoom in on the relative supply of different media contents and distinguish between the supply of political information and entertainment. The question is how to operationalize the relative amount of political information within media environments. It is impossible to evaluate all information supplied by each media source and label it entertainment or political content. Especially newer media sources like the internet constitute nearly endless amounts of information. The supply of information by the internet is transnational which makes it impossible to estimate and distinguish the contents the internet provides in each country. For traditional media on the other hand, the sources of information are limited and better documented. In this thesis the relative supply or political information for television was approximated by including countries relative share of public broadcasting in the analyses. Public broadcasting is often found to be positively associated with larger supplies of hard news than commercial broadcasting (Aalberg et al., 2010). The consumption of hard news is in turn associated with more political knowledge (Curran et al. 2009; Iyengar et al. 2009; Soroka et al. 2013). Political knowledge is an important predictor of political participation (Prior, 2005). It therefore seems plausible that European countries with a larger share of public broadcasting, provide higher amounts of political information. In this study two relative public broadcasting measures were used, which were retrieved from the EAO statistical yearbook i. The first measure is the relative daily TV audience market share of public channels. The other measure is the share of public channels of the total number of channels (terrestrial, cable, satellite, IPTV and mobile combined) within a country. These two measures differ in the sense that the first one is more directly related to individuals consumption choice, because it indicates the preferences of countries TV audiences. The second measure merely indicates the relative supply of public channels regardless of TV audiences. Table 5 shows the descriptive statistics of the public broadcasting measures Control variables Because political participation is strongly related to social background characteristics (Brady et al. 1995, Marien et al. 2010, Stolle & Hooghe, 2011) several control variables were included in the analyses. This enabled testing if media preference effects exist above and beyond the effects of socioeconomic background characteristics. The variables that were controlled for are education, sex, age, income, employment status, marital status, ethnicity, city size and political interest. The operationalisations and properties of these variables are discussed below and descriptive statistics of all control variables are presented in Table 1. 35

36 The ESS questionnaire included two distinct measures of respondents education: the number of completed educational years and a standardized ordinal measure of education (ISCED). I used the International Standard Classification of Education (ISCED) measure in this study. Because European countries educational systems are very different in terms of structure and curricular content, it is difficult to compare the educational levels of citizens from different countries. The ISCED measure is an internationally agreed standardized measure of education, that enables between-country comparisons. In the questionnaire respondents were asked what the highest level of education was that they had successfully completed. The main 9 ISCED answer categories are: ES-ISCED I Less than lower secondary ; ES-ISCED II Lower secondary ; ES-ISCED IIIb Lower tier upper secondary ; ES-ISCED IIIa Upper tier upper secondary ; ES-ISCED IV Advanced vocational, sub-degree ; ES- ISCED V1 Lower tertiary education, BA level ; ES-ISCED V2 Higher tertiary education, MA level ; Other. The 95 respondents with missing values on this variable and respondents in the other category were excluded from the analyses. In Table 1 some descriptive statistics for education are presented. The sex of respondents in the ESS dataset was coded by the interviewer. The data included more women (54.5%) than men (45.5%). There were only 16 missing values on this variable, which were removed from the analyses. Respondents were both asked for their age and their birth year. Respondents age ranged from 14 to 102 years old. Some missing values on the age variable were calculated by subtracting respondents birth year from the survey year. Respondents with an age below 18 were removed from the analyses because this is the minimum voting age in most European countries. In total, 378 cases were removed with either missing values on age or ages below 18. For household income, the same holds as for education: there is strong variation across countries which makes it difficult to compare citizens from different countries. Because of this and to avoid non-response due to the sensitive and personal nature of the question, income was measured in the ESS questionnaire by a decile approach. Respondents were asked to place themselves on a ten-point income scale with country-specific categories. The categories were based on deciles of the actual household income range in the given country. As often is the case with income measures there was a high level of non-response to the income question. Around 20 per cent of the respondents did not have a valid income score, which is not uncommon for this measure. If the analyses were restricted to records with complete income information, the missing data might lead to biased estimates in the analyses. Therefore cases with missing values on income were not removed from the analyses. Instead, income dummies and a missing category were created. 9 Each of these categories contains several country specific subcategories which are not presented here. 36

37 Employment status was measured by asking respondents about their main activities. Respondents were asked what they had been doing for the last seven days and were able to select from the categories: in paid work; in education; unemployed and actively looking for a job; unemployed and not actively looking for a job; permanently sick or disabled; retired; in community or military service; doing housework; other. These answer categories were recoded into a variable with the four categories: employed; unemployed; retired and other. All categories from the original variable that did not match the categories from the new variable were grouped under the other category. The 64 respondents with missing values were excluded from the data. Marital status was measured by presenting respondents a card with descriptions of legal marital statuses and asking them to pick the description that fitted their situation best. They were able to choose from: legally married; in a legally registered civil union; legally separated; legally divorced/civil union dissolved; widowed/civil partner died; none of these (never married or in legally registered civil union). Data for Finland was completely missing for this measure. Another question with roughly the same answer categories was used to predict scores for the Fins on the marital status variable. Some categories did not match very well and only those categories that matched were used to predict the missing values. The remaining 924 missing values were not included in the analyses. Ethnicity was included as a dichotomous variable. A measure was constructed that distinguishes immigrants from native citizens, based on the origin of both mother and father. If both parents were native inhabitants of the country respondents live in, the respondents were considered autochthonous. If either one or both of them were born elsewhere, they were considered immigrants. Respondents with missing information on the origin of both parents were removed from the analyses. Respondents who provided information on only one of their parents, were either included or removed from the analyses depending on whether this one parent was immigrant or not. If this one parent was a native inhabitant the respondent was removed from the analyses because it is unclear if the other parent was a native as well. If this one parent was not a native inhabitant, the respondent was classified as immigrant, regardless of the other parent. Eventually 184 respondents were removed from the analyses due to a lack of information. The measure city size was included as a control variable in the analyses, because it has been found to be a significant predictor of voter turnout in presidential elections (Prior, 2005; Rittenberg et al., 2012). Respondents were asked to pick a description that fitted their habitat best. The categories were: farm or home in countryside; country village; town or small city; suburbs or outskirts of big city; a big city. Only 48 respondents were unable to estimate the size of their habitat and were not included in the analyses. Another important control variable of which the influence was analysed, was a measure of political interest. Previous studies indicated that political interest is a very strong predictor of political 37

38 participation (Brady et al. 1995; Barnes & Kaase, 1979; Tolbert & McNeal, 2003; Rittenberg et al. 2012). It was however unclear whether political interest referred to something substantially different than my RPCP measures. It is likely that these measures correlate very strongly, because politically interested people will probably consume more political content when using media, than politically uninterested people. The political interest measure consisted of the four categories: not at all interested; hardly interested; quite interested; very interested. For 121 respondents no valid answers were recorded. These respondents were removed in the analyses. 3.4 Missing data The unprocessed ESS(2010) data (without Ukraine and Israel) contained respondents. Much of the respondents with missing values on any of the variables described in previous sections were removed from the analyses. First, respondents with invalid scores on the dependent and independent variables were removed. A total of 4345 respondents with missing values on conventional and unconventional participation were excluded. With regard to the media content preference variables, only two respondents with missing values were removed. For these respondents the calculation of the combined RPCP measure was impossible. To avoid removal of the high amount of missing values on the separate RPCP measures (nearly 50%), missing preference categories were included in the analyses. Most of the respondents with missing values on the control variables were removed from the analysis. However, for some variables missing values were predicted by using other variables. For the income variable dummy coding was used and a missing dummy was included, because one fifth of the respondents refused to reveal their income. In total, 1796 respondents with missing values on the control variables that could not be predicted were excluded from the analyses. The exclusion of missing values for all variables combined resulted in the total removal of 6141 respondents which was 12,7 % of the ESS(2010) data. 38

39 Chapter 4 Analyses and results 4.1 Research methods The effects of individual preferences and the media environment on political participation were analyzed across 25 European countries. Multilevel binomial logistic regression models were fitted to the data to account for both individual-level and contextual-level influences on the outcome variables of political participation. The approximated intra-country correlations of the dependent variables, voting (0,08), party work or membership (0,07) and unconventional participation (0,18) indicated the variance that was attributed to the country-level, justifying the use of multilevel analyses 10. The analyses were conducted in two stages. In the first stage dummy variables of media content preferences were analyzed because the media content preference variable was not linearly related to the log odds of the different modes of political participation. A likelihood ratio test (not presented) showed a better data fit of a model with media content preference dummies compared to a model in which media content preference was included as interval variable. In the first regression model (table 7a), only the media content preference dummy variables were included, to explore the bivariate relationship between the main predictor media content preferences and political participation. Subsequently the control variables, country-level characteristics and cross-level interactions were added in models 2, 3 and 4 (table 8-13). The three types of political participation were analyzed separately. Several additional models have been estimated which are only presented in Appendix B. In the second stage of the analyses, all regression models were estimated again, but with an interval media content preference variable. Although media content preferences did not linearly relate to the of the dependent political participation variables, including content preferences as a quasi-metric variable simplified the interpretation of the results. The coefficients presented in all regression models are unstandardised regression coefficients. 10 The intra-class correlations were approximated by simulating the distribution of u0j (Rodriguez & Elo, 2003). 39

40 4.2 Results Relative political content preferences and political participation The bivariate relationships between the different modes of political participation and the main predictor media content preference were estimated in the first model (table 7a). Media content preferences were subdivided into six categories: Only entertainment, mostly entertainment, equal preference, mostly politics, only politics and missing preference. These categories were included as dummy variables in the regression model and the category equal preference was set as the reference category. The interpretation of the ß-coefficients in table 7a is as follows. Take voting for example, the intercept (1,602) refers to the category). The of people with an equal media content preference (reference or log odds, is the natural logarithm of the odds. The odds refer to the probability of voting divided by the probability of not voting and can be calculated by. Using the odds, the probability to vote is calculated as follows: odds i / (1+odds i ). The probability to vote for people with an equal preference for entertainment and politics is therefore: The ß-coefficients of the other media content preference categories refer to the difference in with the reference category. The calculation of the probability to vote for people with an only entertainment preference is therefore as follows. The or log odds is 0,242 (1,602-1,360) and the odds are. The probability to vote for people with a preference for only entertainment is therefore: The hypothesis regarding the relationship between media content preferences and political participation was that: H1a: The higher peoples relative preference for political media content, the more likely they are to engage in political participation. The coefficients in table 7a show a pattern that mostly supports hypothesis H1a. The dummy variables are ordered from the lowest preference for political media content (only entertainment) to the highest preference for political media content (only politics). Therefore the lowest ß-coefficients (and probabilities) were expected for people who prefer only entertainment and the highest for people who prefer only politics. Preferences for only or mostly entertainment showed negative ß- 40

41 coefficients, meaning that having a preference for entertainment is associated with lower probabilities to participate politically than having an equal preference for entertainment and political media content. Preferences for only or mostly politics on the other hand, are in most cases (except for voting) associated with positive ß-coefficients. People with a preference for political media content are thus more likely to participate politically than people with an equal preference. The ß-coefficients for only entertainment are lower than the ß-coefficients for mostly entertainment, indicating that preferences for only entertainment are associated with lower logits and therefore lower probabilities to vote than preferences for mostly entertainment. The political preference coefficients do not entirely follow the expected pattern. People with a mostly politics preference have a higher probability (0.85) to vote than people with a who only prefer political media content (0.78). Table 7a shows negative ß-coefficients for people with missing media content preferences for all modes of political participation. These are people who do not use television, radio or newspapers at all. Their probabilities to participate politically are lower than for people with an equal preference. For both party work or membership and unconventional participation all ß-coefficients have relative sizes that support hypothesis H1a so far. However, bivariate analyses with only media content preferences as predictors might suffer from omitted variable bias. Therefore no conclusions regarding the hypothesis are drawn yet, based on these simple bivariate relationships. Table 7a. Model 1: unstandardised logistic regression parameter estimates of different modes of political participation on media content preferences. Voting Party work or membership Unconventional participation ß S.E. Sig. ß S.E. Sig. ß S.E. Sig. Intercept 1,602 0,108-2,527 0,101-0,936 0,162 Relative content preference (ref = equal preference) Only entertainment -1,360 0,055 ** -1,179 0,149 ** -0,769 0,070 ** Mostly entertainment -0,409 0,034 ** -0,561 0,053 ** -0,370 0,031 ** Mostly politics 0,136 0,047 ** 0,226 0,060 ** 0,068 0,038 * Only politics -0,351 0,056 ** 0,286 0,078 ** 0,199 0,051 ** Missing preference -1,391 0,124 ** -0,875 0,340 ** -0,576 0,174 ** Number of observations Number of countries Loglikelihood 43488, , ,4 ** P < 0,01, * p < 0,05 (two-tailed) Source: ESS(2010) 41

42 4.2.2 Media-specific content preferences The ESS(2010) data contained content preference information for different media types, which enabled the analysis of media-specific preferences. The use of general media content preference measures (table 7a) is subject to the implicit assumption that people have a consistent preference for either entertainment or politics that does not differ across media types. It might, however, be the case that content preferences differ across media types and have different relationships with political participation. Reading about politics in newspapers, for example, might be more strongly related to political participation than watching the news on television. Therefore, the general media content preference measures were replaced by more fine-grained preference measures in an additional analysis (table 7b). For television, radio and newspaper, six dummy variables for the media content preference categories were created. These categories were again: Only entertainment, mostly entertainment, equal preference, mostly politics, only politics and missing preference. The high amount of missing values on all media-specific preferences necessitated the inclusion of missing value categories in order to maintain acceptable sample sizes. For all media content preference dummy variables, the reference category was set to equal preference. The hypothesis regarding media-specific content preferences read: H1b: The associations between relative media content preferences and political participation vary across media types. The analysis with media-specific content preferences (table 7b) showed a more nuanced picture of how content preferences were related to political participation. The general pattern that can be observed in table 7b, is that people with a preference for political media content for the media radio or newspaper, were less likely to participate either conventionally or unconventionally than people with an equal preference. For radio however, no significant coefficients for political content preferences were observed for party work or membership and unconventional political participation. Another exceptional finding was that people with an only politics preference for newspaper, were more likely to participate unconventionally than people with an equal preference. Television was the only medium for which the content preferences showed roughly the same pattern as the general media content preference measures. A preference for political media content (whether it was mostly or only politics), was associated with negative ß-coefficients for voting and positive ß-coefficients for party work or membership and unconventional participation. This means that compared to having an equal preference for entertainment and political media content, a preference for mostly or only political media content is associated with lower probabilities to vote and higher probabilities to participate in the other modes of political participation. People with a missing preference -mostly because they did not use the medium at all- were often less likely to 42

43 engage in any kind of political participation than people with an equal preference. Only people with a missing media content preference for television were more likely to participate unconventionally than people with an equal preference. Table 7b. Unstandardised regression parameter estimates of voting, party work or membership and unconventional political participation on media-specific relative content preferences. Voting Party work or membership Unconventional participation ß S.E. Sig. ß S.E. Sig. ß S.E. Sig. Intercept 2,437 0,169-1,891 0,179-0,874 0,188 Television (ref = equal preference) Only entertainment -0,944 0,055 ** -0,613 0,126 ** -0,225 0,061 ** Mostly entertainment -0,344 0,040 ** -0,396 0,061 ** -0,201 0,036 ** Mostly politics 0,020 0,055 0,096 0,073 0,092 0,046 ** Only politics -0,246 0,050 ** 0,221 0,069 ** 0,217 0,044 ** Missing preference -0,634 0,067 ** 0,181 0,111 0,481 0,067 ** Radio (ref = equal preference) Only entertainment -0,556 0,076 ** -0,289 0,112 ** -0,168 0,066 ** Mostly entertainment -0,298 0,071 ** -0,205 0,097 ** -0,106 0,059 * Mostly politics -0,189 0,093 ** 0,025 0,122 0,029 0,076 Only politics -0,276 0,075 ** -0,016 0,100-0,033 0,062 Missing preference -0,596 0,072 ** -0,281 0,101 ** -0,426 0,062 ** Newspaper (ref = equal preference) Only entertainment -0,705 0,117 ** -0,908 0,153 ** -0,347 0,101 ** Mostly entertainment -0,132 0,115-0,336 0,131 ** 0,031 0,094 Mostly politics 0,098 0,134-0,081 0,147-0,011 0,107 Only politics -0,270 0,113 ** -0,330 0,128 ** 0,186 0,093 ** Missing preference -0,747 0,113 ** -1,086 0,134 ** -0,287 0,094 ** Number of observations Number of countries Loglikelihood 42819, , , 2 ** P < 0,01, * p < 0,05 (two-tailed) Source: ESS(2010) The results provided only weak support for hypothesis (H1b) that content preferences vary across media and have media-specific effects. For voting, the different media content preferences showed similar patterns across the different media types. People with a (mostly or only) preference for political media content were in most cases less likely to vote than people with an equal preference. For the other two modes of political participation, some differences were observed across media types. Having a preference for political media content showed different ß-coefficients across media 43

44 types, for political party work or membership. Having a political content preference compared to an equal preference for television, increased the probability to do party work or be a member. For radio no difference was found, while for newspaper this preference was associated with a lower probability to do party work or be a member. People with political content preferences for television and newspaper were more likely to participate unconventionally than people with an equal preference. The media-specific preference measures were not included in the rest of the regression models for two main reasons. Firstly, the missing categories for the separate media types contained many respondents. Nearly half of the respondents did not have a valid preference score for any of the different media types. Secondly, the media-specific preference measures are more difficult to interpret than the combined media preference measure. The single general media preference measure does not suffer from such a high amount of missing values, because a valid score on any of the media type preferences resulted in a valid combined media preference measure. Furthermore, the use of a combined media preference measure simplifies the interpretation of the results and provided a more parsimonious regression model. Therefore the single media preference measures were included in the following regression models Controlling for individuals backgrounds In the first regression model (table 7a) the expected associations between media content preferences and political participation were visible. A relative preference for political media content was positively associated with political participation. In the next model (table 8) control variables were added to the regression equation, to test whether the significant associations were related to individuals background characteristics and reduce the chance of omitted variable bias. The control variables were: education, gender, age, employment status, marital status, income, ethnicity and city size. Also a quadratic transformation of age was included in the regression models to account for the curvilinear relationships of age with two of the dependent variables. The coefficients for the education dummy variables showed a very clear positive relationship between educational attainment and the three different modes of political participation. For all kinds of political participation, the ß-coefficients were lowest for the lowest level of education (less than lower secondary) and increased a little with every higher level of education. This means that people s level of education was positively related to the probability to engage in any kind of political participation. Men were less likely to vote and participate unconventionally than women. They were however, more likely to be a member of, or work for a political party. Age was positively associated with all modes of political participation. The significant coefficients of age² indicated that the relationships between age and voting and age and unconventional participation were curvilinear. The 44

45 employment status dummy variables showed significant voting differences between employed, unemployed and retired people. Retired people were most likely to vote, followed by employed and unemployed. People in the other category were more likely than employed people to participate unconventionally. Significant associations were also found for marital status. Married people (reference category) were the most likely to vote, compared to people with other relationship statuses. Divorcees, people with a civil union arrangement and people who never married were more likely to engage in unconventional political activities, compared to married people. With regard to the relation between party work or membership and marital status it was found that widows were less likely to participate than married people. Ethnic minorities were less likely to participate in any kind of political activity, than the ethnic majority. With respect to the size of people s place of residence, different associations were found for different types of participation. People from farm homes and country villages were more likely to vote than people living in a town or small city. People living in big cities were less likely to vote than people living in towns or small cities. For unconventional political participation the opposite pattern can be observed. People from big cities and the suburbs are more likely to participate than people from towns or small cities. Party work or membership was more likely among people living in the countryside than among people living in towns or small cities. Living in a big city reduces the probability to work for or be member of a political party, compared to living in a town or small city. Finally, the income dummy variables showed that people with high incomes (6 th decile or higher) were more likely to vote than people in the 5 th income decile. People in the lowest decile are less likely to vote than people in the 5 th decile. Only one income dummy showed a significant difference with the reference category regarding political party work or membership. People with the highest income were more likely to be a member of or work for a political party. Unconventional participation was found to be less likely among people in the lowest three income deciles, compared to the 5 th decile. The inclusion of control variables in the regression models did not affect the associations between relative media preferences and political participation much. Nearly all associations observed in model 1 (table 7a) remained relatively unchanged, meaning that the significant relationships between media preferences and political participation are not affected by confounding background characteristics. The first hypothesis was that: H1a: The higher peoples relative preference for political media content, the more likely they are to engage in political participation. This hypothesis was supported for political party work or membership and unconventional participation. The relationships between the relative media content preference dummy variables and voting show an odd pattern. Nearly all content preferences are ordered in a way that a higher 45

46 relative preference for political media content is associated with a higher probability to vote. The only exceptions were people with the highest preference for political media content. These people were less likely to vote than people with an equal preference The influence of political interest In a second additional analysis (table 8b, appendix B) a control variable was added to the model to test for the influence of a possible confounding factor: political interest. Political interest has been identified as a strong predictor of political participation in previous research (Brady et al., 1995). It was expected to correlate with media preferences. Politically interested people are probably more likely to have a preference for political media content. Without controlling for political interest, the model might suffer from omitted variable bias and the coefficients of the relative preference measures might be overestimated. In the worst case, the relationship between relative content preferences and political participation is a spurious one. Table 7b showed, however, that political participation is associated with relative media content preferences above and beyond the influence of political interest. Although weakened, most of the media content preference coefficients remained significant when political interest was added to the model. Examination of VIF statistics showed no signs of multicollinearity among the predictors in the regression model (VIF <2). Nevertheless, political interest was not included in the main regression models for methodological reasons. A preference for political media content and political interest in general, are conceptually very closely related to each other. Political interest is a an all-encompassing general concept that includes every activity related to politics, also political media consumption. Therefore, the extent to which the two concepts refer to different phenomena is unclear. The inclusion of both political interest and political media content preferences in the analyses might weaken the media content preference estimates while not adding much insights to the model theoretically. 46

47 Table 8. Model 2: unstandardised logistic regression parameter estimates of voting, party work or membership and unconventional political participation on relative media content preferences controlled for education, gender, age, employment status, marital status, income, ethnic minority and city size. Voting Party work or membership Unconventional participation ß S.E. Sig. ß S.E. Sig. ß S.E. Sig. Intercept 2,074 0,130-2,794 0,136-0,706 0,179 Relative content preference (ref = 3. equal preference) 1. Only entertainment -0,902 0,058 ** -0,853 0,151 ** -0,690 0,073 ** 2. Mostly entertainment -0,256 0,035 ** -0,424 0,054 ** -0,333 0,032 ** 4. Mostly politics 0,087 0,048 * 0,148 0,061 ** 0,035 0, Only politics -0,244 0,059 ** 0,281 0,079 ** 0,134 0,053 ** Missing preference -0,997 0,131 ** -0,657 0,344 * -0,509 0,185 ** Education (ref = 4. upper tier secondary) 1. Less than lower secondary -0,531 0,050 ** -0,549 0,090 ** -0,869 0,056 ** 2. Lower secondary -0,463 0,041 ** -0,327 0,078 ** -0,498 0,045 ** 3. Lower tier upper secondary -0,364 0,043 ** -0,285 0,079 ** -0,265 0,042 ** 5. Advanced vocational 0,122 0,046 ** 0,030 0,076 0,141 0,043 ** 6. Lower tertiary education 0,390 0,055 ** 0,337 0,076 ** 0,406 0,046 ** 7. Higher tertiary education 0,462 0,051 ** 0,397 0,072 ** 0,497 0,044 ** Gender (ref=female) -0,100 0,026 ** 0,507 0,044 ** -0,054 0,026 ** Age 0,231 0,013 ** 0,132 0,021 ** -0,084 0,013 ** Age² -0,041 0,005 ** 0,010 0,008-0,045 0,005 ** Employment status (ref = employed) Unemployed -0,349 0,046 ** -0,135 0,100-0,008 0,053 Retired 0,113 0,048 ** -0,033 0,074 0,067 0,047 Other -0,059 0,037-0,008 0,071 0,112 0,038 ** Marital status (ref = married) Civil union -0,709 0,119 ** -0,404 0,248 0,209 0,117 * Separated -0,304 0,133 ** 0,130 0,233-0,023 0,135 47

48 Table 8. continued Voting Party work or membership Unconventional participation ß S.E. Sig. ß S.E. Sig. ß S.E. Sig. Divorced -0,489 0,044 ** -0,019 0,079 0,100 0,044 ** Widowed -0,405 0,048 ** -0,215 0,087 ** -0,077 0,055 Never married -0,290 0,037 ** -0,031 0,064 0,112 0,036 ** Income (ref = 5th decile) 1st decile -0,181 0,061 ** 0,022 0,111-0,239 0,065 ** 2nd decile -0,044 0,060-0,086 0,106-0,192 0,061 ** 3rd decile -0,079 0,061-0,019 0,103-0,166 0,060 ** 4th decile -0,056 0,061-0,029 0,102-0,024 0,058 6th decile 0,113 0,063 * 0,086 0,100 0,002 0,058 7th decile 0,137 0,065 ** 0,088 0,100 0,061 0,057 8th decile 0,118 0,067 * 0,012 0,104 0,073 0,059 9th decile 0,099 0,072 0,012 0,108 0,028 0,062 10th decile 0,178 0,074 ** 0,302 0,101 ** 0,040 0,062 Missing income -0,056 0,053-0,020 0,089-0,183 0,051 ** Ethnic minority (ref=no) -0,736 0,036 ** -0,248 0,072 ** -0,188 0,039 ** City size (ref = 3. town or small city) 1. Farm or home in country side 0,136 0,063 ** 0,491 0,084 ** 0,038 0, Country village 0,169 0,032 ** 0,035 0,055-0,204 0,033 ** 4. Suburbs 0,021 0,045-0,085 0,074 0,175 0,042 ** 5. A big city -0,074 0,035 ** -0,179 0,063 ** 0,173 0,036 ** Number of observations Number of countries loglikelihood 40641, , ,9 ** P <.01, * p <.05 (two-tailed) Source: ESS(2010) 48

49 4.2.5 Political participation across different media environments In model 3 (table 10) four contextual level characteristics were added to the regression model to test for the direct influence of countries media environments on political participation. These four characteristics were broadband internet penetration, the total number of television channels, the channel share of public broadcasting and public channels audience shares. All four country-level characteristics were included simultaneously, since there were no signs of multicollinearity (table 9, Appendix B). Looking back at the theory, the first two country-level characteristics broadband internet and number of television channels were operationalisations of the absolute amounts of information supplied by media environments 11. Higher scores on these variables indicate high absolute levels of entertainment and political content supplied within a country. The expectation regarding these characteristics was that: H2a: The absolute amount of information that is provided within media environments, does not affect political participation. Table 10 shows that countries broadband internet penetration rates were positively associated with all modes of political participation. The more widespread a country s access to online information, the more citizens participated in politics. This is not in line with hypothesis 2a, which stated that the total amount of information supply within media environments does not directly affect political participation. The total number of television channels was negatively related to party work or membership. The more television channels are available within a country, the less likely its citizens are to work for, or be a member of a political party. This finding also refutes hypothesis H2a. Next to broadband internet penetration rates and the number of television channels, two other contextual characteristics were included in the analyses: the channel share of public broadcasting and public channels audience shares. These two characteristics refer to the relative information or content supply within media environments. Contrary to the other two characteristics, these variables contain information on the type of contents supplied and are proxies for the relative share of political content within the total supply of information. Countries with a high score on these variables are assumed to have a high supply of political information and thereby automatically a low supply of entertainment. It was expected that: H2b: The relative amount of political information that is supplied within media environments positively affects political participation. 11 It is important to emphasize that this variable of information supply refers to the supply of both political and entertainment contents. 49

50 The results (table 10), however, show only limited support for this hypothesis. No significant associations between the relative supply of political information and conventional modes of political participation were found. Only unconventional political participation was positively associated with the public broadcasters audience shares within countries media environments. An increase of one percentage point of public broadcasters audience shares was associated with an increase in of 0,018 (table 10). Higher relative amounts of political information within the total amount of contents supplied by media environments, were associated with higher probabilities to participate unconventionally (in boycotts, demonstrations and petitions). 50

51 Table 10. Model 3: Unstandardised logistic regression parameter estimates of voting, party work or membership and unconventional participation on contextual-level media environment characteristics. 12 Voting Party work or membership Unconventional participation ß S.E. Sig. ß S.E. Sig ß S.E. Sig Intercept 2,043 0,118-2,825 0,130-0,742 0,120 Relative content preference (ref = 3. equal preference) 1. Only entertainment -0,901 0,058 ** -0,846 0,151 ** -0,689 0,073 ** 2. Mostly entertainment -0,255 0,035 ** -0,421 0,054 ** -0,333 0,032 ** 4. Mostly politics 0,086 0,048 * 0,146 0,061 ** 0,034 0, Only politics -0,244 0,059 ** 0,280 0,079 ** 0,134 0,053 ** Missing preference -0,995 0,131 ** -0,650 0,344 * -0,507 0,185 ** Contextual level Broadband penetration rate 0,015 0,007 ** 0,012 0,005 ** 0,031 0,007 ** Total number of television channels -0,001 0,001-0,001 0,001 * 0,001 0,001 Public broadcasting audience shares 0,012 0,010 0,001 0,008 0,018 0,010 * Public broadcasting channels shares -0,009 0,010-0,004 0,008-0,006 0,010 Number of observations Number of countries loglikelihood 40634, ,4 ** P <.01, * p <.05 (two-tailed) Sources: ESS(2010) and EAO(2010) 12 Control variables were also included in these models but not presented here. For full tables see Appendix A. 51

52 4.2.6 Cross-level interaction effects of the media environment To answer the third research question to what extent the effects of media content preferences on political participation vary across European countries media environments, the contextual characteristics were interacted with the media content preference dummies in model 4 (table 11, 12 and 13). Different relationships were expected for absolute and relative information supply by media environments, which will be discussed in the next sections a RPCP and absolute content availability The total amount of information provided within media environments was expected to be positively related to the choice that media users have to consume the content they prefer. People who prefer to consume political media content choose to increasingly do so when more information is available and hence participate in politics even more so. Therefore the first hypothesis regarding the crosslevel interaction of absolute media content availability with the association between content preferences and political participation, read: H3a: The absolute amount of information that is provided within media environments, strengthens the positive relations between relative political content preferences and political participation. With regard to voting, no significant cross-level interactions of the absolute information supply with political content preferences were observed (table 11). The same holds for unconventional political participation (table 13). For political participation in the form of party work or membership on the other hand, positive cross-level interactions were found (table 12). Both a mostly and only preference for political media content were positively associated with countries broadband internet penetration rates. This means the probability of people with a preference for political media content to work for, or be a member of a political party was higher in countries with higher broadband internet penetration rates. People with a preference for political content are increasingly able to consume this content, when more broadband internet is available in their country. They become more politically knowledgeable and hence participate more politically. Hypothesis H3a therefore only holds for political party work or membership. For people with a mostly entertainment or only entertainment content preference, both positive and negative interactions with the absolute supply of information were found. For voting the evidence was mixed. A positive interaction of the number of television channels and a negative interaction of broadband internet with an only entertainment preference were found (table 11). This means that the negative association between a preference for entertainment and voting, compared to the reference category, weakens, instead of strengthens, when the number of channels increases. The difference between people who only prefer entertainment and people with an equal 52

53 preference increases when broadband internet penetration rates increase. People with a preference for only entertainment were less likely to vote in countries that have media environments with higher broadband internet penetration. For both party work or membership and unconventional political participation, other positive cross-level interactions of the absolute media content supply were found (table 12 and 13). Here, broadband internet penetration rates were positively related to a mostly entertainment preference. This means that the difference in 53 between people who mostly prefer entertainment and people with an equal preference for entertainment and political media content, decreases with an increasing penetration rate of broadband internet. Looking at party work or membership, the positive ß-coefficient for the interaction of broadband internet penetration rates with a mostly entertainment content preference (0,007), indicates that the for people with a mostly entertainment preference, increases with increasing broadband internet penetration rates. This increase in political party, also increases. means that the probability of these people to work for, or be a member of a For unconventional participation, the number of television channels was negatively associated with an only entertainment preference (table 13). This means that the difference in between people with an only entertainment preference and people with an equal preference, increases with an increasing amount of television channels in a country. The people with an only entertainment preference, decreases with an increasing amount of television channels, meaning that they are less likely to participate unconventionally when the amount of television channels increases. According to the theory, this is because an increasing number of television channels enables people to select the television content they prefer and avoid (political) media content they are not interested in b RPCP and relative political media content availability A positive relationship of the relative availability of political media content with political preferences was expected. In countries with a high relative availability of political information, the positive effect of a preference for political content on political participation was expected to be stronger. This means that a relatively higher availability of political information should enable people with a preference for political media content to better correspond their media consumption with their preferences and become more politically knowledgeable and hence more likely to participate politically. Therefore the hypothesis read: H3b. The relative amount of political information within media environments, strengthens the positive relationships between relative political content preferences and political participation. for

54 The results are in favor of this hypothesis with regard to the conventional modes of political participation. A positive interaction was found of public broadcasting audience shares with a mostly politics preference for voting (table 11). The association between a mostly preference for political media contents and voting is stronger in countries with higher public broadcasting audience shares. Furthermore, a positive interaction was found of public broadcasting channel shares with an only politics preference for political party work or membership (table 12). People with a preference for political media contents are more likely to work for or be a member of a political party in countries where public broadcasting comprises a higher share of the television channels. No significant interactions were found for unconventional political participation. The regression results regarding the interactions between the relative amount of political information and entertainment preferences were mixed. For voting, a negative cross-level interaction term was observed (table 11). The public broadcasting channel shares of countries are negatively associated with an only entertainment preference. This means that when the relative amount of political information increases in a country, people who prefer entertainment are less likely to vote. For party work or membership (table 12) no significant cross-level interactions were found. The empirical evidence regarding unconventional political participation was mixed (table 13). For this mode of participation positive associations of public broadcasting channel shares with a mostly entertainment preference were observed. This means that the negative association between a preference for entertainment and unconventional political participation is weakened by the presence of public broadcasting. In other words, people who mostly prefer entertainment, are more likely to participate unconventionally when the share of political information within their media environment increases. A negative association was found between public broadcasting audience shares and an only entertainment preference. People who only prefer entertainment are less likely to participate unconventionally when the public broadcasters within a country have higher audience shares. Here the negative association between a preference for entertainment and unconventional political participation is strengthened. 54

55 Table 11. Model 4: unstandardised logistic regression parameters of voting on contextual-level media environment characteristics and cross-level interaction terms. 13 Model 4 - Voting ß S.E. Sig ß S.E. Sig ß S.E. Sig ß S.E. Sig Intercept 2,048 0,120 2,078 0,131 2,072 0,125 2,067 0,129 Relative content preference (ref = 3. equal preference) 1. Only entertainment -0,932 0,060 ** -0,910 0,058 ** -0,912 0,059 ** -0,946 0,059 ** 2. Mostly entertainment -0,259 0,035 ** -0,256 0,035 ** -0,257 0,035 ** -0,256 0,035 ** 4. Mostly politics 0,082 0,048 * 0,087 0,048 * 0,087 0,048 * 0,082 0,048 * 5. Only politics -0,240 0,059 ** -0,243 0,059 ** -0,244 0,059 ** -0,242 0,059 ** Missing preference -0,984 0,132 ** -0,996 0,131 ** -0,998 0,131 ** -0,991 0,131 ** Contextual level Broadband penetration rate 0,016 0,007 ** 0,015 0,007 * 0,015 0,007 * 0,015 0,007 * Total number of television channels -0,001 0,001-0,001 0,001-0,001 0,001-0,001 0,001 Public broadcasting audience share 0,011 0,010 0,012 0,010 0,011 0,010 0,011 0,010 Public broadcasting channels share -0,009 0,010-0,009 0,010-0,009 0,010-0,007 0,010 Crosslevel interactions with relative content preferences (ref=3. equal preference) 1. Only entertainment -0,006 0,003 * 0,001 0,000 * -0,003 0,005-0,024 0,006 ** 2. Mostly entertainment -0,002 0,002 0,000 0,000-0,001 0,003-0,001 0, Mostly politics 0,003 0,003 0,000 0,000 0,009 0,004 ** 0,003 0, Only politics 0,004 0,003 0,000 0,000 0,002 0,005-0,004 0,004 Number of observations Number of countries loglikelihood ** P <.01, * p <.05 (two-tailed) Source: ESS(2010) 13 The contextual-level predictor that is interacted with the relative media content preferences is highlighted in each model. 55

56 Table 12. Model 4: unstandardised logistic regression parameters of party work or membership on contextual-level media environment characteristics and cross-level interaction terms. 14 Model 4 - Party work or membership ß S.E. Sig ß S.E. Sig ß S.E. Sig ß S.E. Sig Intercept -2,805 0,130-2,825 0,130-2,821 0,130-2,820 0,130 Relative content preference (ref = 3. equal preference) 1. Only entertainment -0,841 0,153 ** -0,845 0,152 ** -0,836 0,154 ** -0,847 0,152 ** 2. Mostly entertainment -0,446 0,055 ** -0,422 0,055 ** -0,426 0,055 ** -0,429 0,055 ** 4. Mostly politics 0,116 0,064 * 0,150 0,062 ** 0,130 0,062 ** 0,133 0,062 ** 5. Only politics 0,214 0,084 ** 0,293 0,080 ** 0,271 0,081 ** 0,253 0,081 ** Missing preference -0,729 0,345 ** -0,650 0,344 * -0,660 0,345 * -0,668 0,344 * Contextual level Broadband penetration rate 0,006 0,006 0,012 0,005 ** 0,012 0,005 ** 0,012 0,005 ** Total number of television channels -0,001 0,001 * -0,001 0,001-0,001 0,001 * -0,001 0,001 * Public broadcasting audience share 0,001 0,008 0,001 0,008-0,001 0,008 0,001 0,008 Public broadcasting channels share -0,004 0,008-0,004 0,008-0,004 0,008-0,008 0,008 Crosslevel interactions with relative content preferences (ref=3. equal preference) 1. Only entertainment 0,014 0,009 0,000 0,001 0,008 0,013 0,010 0, Mostly entertainment 0,007 0,003 ** 0,000 0,000 0,000 0,004 0,003 0, Mostly politics 0,007 0,004 * 0,000 0,001 0,007 0,005 0,005 0, Only politics 0,014 0,005 ** 0,001 0,001 0,005 0,006 0,010 0,005 * Number of observations Number of countries loglikelihood ** P <.01, * p <.05 (two-tailed) Source: ESS(2010) 14 The contextual-level predictor that is interacted with the relative media content preferences is highlighted in each model. 56

57 Table 13. Model 4: unstandardised logistic regression parameters of unconventional participation on contextual-level media environment characteristics and cross-level interaction terms. 15 Model 4 - Unconventional participation ß S.E. Sig ß S.E. Sig ß S.E. Sig ß S.E. Sig Intercept -0,726 0,121-0,743 0,120-0,740 0,120-0,736 0,120 Relative content preference (ref = 3. equal preference) 1. Only entertainment -0,705 0,073 ** -0,661 0,073 ** -0,715 0,074 ** -0,698 0,073 ** 2. Mostly entertainment -0,357 0,033 ** -0,332 0,032 ** -0,340 0,033 ** -0,338 0,032 ** 4. Mostly politics 0,037 0,043 0,034 0,040 0,044 0,041 0,027 0, Only politics 0,127 0,056 ** 0,135 0,053 ** 0,135 0,055 ** 0,125 0,054 ** Missing preference -0,534 0,184 ** -0,507 0,185 ** -0,512 0,184 ** -0,519 0,185 ** Contextual level Broadband penetration rate 0,028 0,007 ** 0,031 0,007 ** 0,031 0,007 ** 0,031 0,007 ** Total number of television channels 0,001 0,001 0,002 0,001 0,001 0,001 0,001 0,001 Public broadcasting audience share 0,018 0,010 * 0,018 0,010 * 0,016 0,010 0,018 0,010 * Public broadcasting channels share -0,006 0,010-0,006 0,010-0,006 0,010-0,009 0,011 Crosslevel interactions with relative content preferences (ref=3. equal preference) 1. Only entertainment -0,001 0,004-0,001 0,000 ** -0,011 0,007 * 0,001 0, Mostly entertainment 0,005 0,002 ** 0,000 0,000 0,004 0,003 0,004 0,002 * 4. Mostly politics 0,000 0,003 0,000 0,000-0,003 0,003 0,004 0, Only politics 0,001 0,003-0,001 0,000 0,000 0,004 0,004 0,003 Number of observations Number of countries loglikelihood ** P <.01, * p <.05 (two-tailed) Source: ESS(2010) 15 The contextual-level predictor that is interacted with the relative media content preferences is highlighted in each model. 57

58 4.3 Summary of the results The high number of regression models with multiple dependent variables and contextual characteristics, has cluttered the overview of the results and complicated the interpretation. Therefore an overview of the hypotheses and empirical evidence is presented in table 14. The hypotheses and the most important outcomes of the analyses are briefly summarized here. H1a: The higher peoples relative preference for political media content, the more likely they are to engage in political participation. This hypothesis found support for all modes of political participation. People with a preference for political media content, participate more politically than people with an equal preference for both entertainment and political media content. However, for voting the evidence was mixed. An only politics preference was negatively associated with voting. H1b: The associations between relative media content preferences and political participation vary across media types. This hypothesis was weakly supported by the data for all modes of political participation. The analyses showed different associations between content preferences for different media types and different modes of political participation. Because of the large amount of missing values and for reasons of interpretability, the media-specific content preference measures were not included in further analyses. H2a: The absolute amount of information that is provided within media environments, does not affect political participation. This hypothesis was rejected since several significant associations of absolute information supply indicators with political participation were found. Broadband internet penetration rates positively affected all modes of political participation, which contradicts the hypothesis. Furthermore, a negative association between the number of television channels within a country and political party work or membership were observed. H2b: The relative amount of political information that is supplied within media environments, positively affects political participation. The relative amount of political information was weakly associated with unconventional political participation. For one of the two indicators (public broadcasting audience shares) a positive 58

59 association with unconventional participation was found. Voting and party work or membership were not associated with the relative amount of political information. Therefore hypothesis H2b is weakly supported by the data. H3a: The absolute amount of information that is provided within media environments, strengthens the positive relations between relative political content preferences and political participation. Hypothesis H3a was weakly supported by the data. The associations between political content preferences and party work or membership were positively related to broadband internet penetration rates. The association between political content preferences and voting and unconventional participation were not related to the total amount of information within media environments. H3b: The relative amount of political information within media environments, strengthens the positive relations between relative political content preferences and political participation. The results showed that the positive associations between political content preferences and conventional political participation, were strengthened by the relative amount of political information within media environments. The associations between political content preferences and unconventional political participation were not affected. This means that if the share of political information that is supplied by a media environment increases, people with a preference for political media content will become more likely to vote and work for a political party, but remain unchanged in their tendency to participate politically in unconventional ways. 59

60 Table 14. Overview of hypotheses and empirical evidence from analyses with media content preference dummy variables. Hypotheses: Relative media content preferences H1a: The higher peoples relative preference for political media content, the more likely they are to engage in political participation. H1b: The associations between relative media content preferences and political participation vary across media types. The media environment H2a: The absolute amount of information that is provided within media environments, does not affect political participation. H2b: The relative amount of political information that is supplied within media environments, positively affects political participation. Interactions of the media environment with media content preferences H3a: The absolute amount of information that is provided within media environments, strengthens the positive relations between relative political content preferences and political participation. H3b: The relative amount of political information within media environments, strengthens the positive relations between relative political content preferences Conventional political participation Party Voting work/membership Unconventional political participation (+/-) (+) (+) (+) (+) (+) (-/0) (-) (-/0) (0) (0) (+/0) (0) (+/0) (0) (+/0) (+/0) (0) and political participation. *0=no empirical evidence; + = only evidence supporting hypothesis; - = only evidence refuting hypothesis; +/- = conflicting empirical evidence; +/0 = weak support for hypothesis; -/0 = weak evidence refuting hypothesis. 60

61 4.4 Additional analyses The use of dummy variables for media content preferences has complicated the interpretation of the results. In the overview of the hypotheses and empirical evidence (table 14) several conflicting findings are visible. The empirical evidence regarding the first hypothesis for example, is mixed. All media content preference dummy variables, except for one (only politics), were related to voting in the expected way. Four of the five media content preference dummies show a pattern that supports hypothesis H1a, but the highest preference for political media content contradicts the hypothesis. Although, the dummy variables paint a nuanced picture of how different media preferences relate to voting probabilities, this nuance goes at the expense of the interpretability of the results and complicate the answers to the hypotheses. For this reason, extra analyses were conducted in which media content preferences were included as an interval variable. This variable ranged from 0 to 1, with 0 indicating a preference for only entertainment and no political media content and 1 indicating a preference for only political media content and no entertainment. From this point forward this measure is referred to as relative political content preference. Although these regression models do not fit the data best, they simplify the relationships between media content preferences and the different modes of political participation and increase the interpretability of the results. Models 1 to 4 were re-estimated with an interval media content preference variable and described here Relative media content preferences and political participation In model 1 (table 15) the three modes of political participation were regressed on the interval measure of relative political content preferences. The measure of relative political content preference is positively associated with all modes of political participation, meaning that the more people prefer political media content over entertainment, the more likely they are to engage in any kind of political participation. 61

62 Table 15. Model 1: unstandardised logistic parameter estimates of voting, party work or membership and unconventional political participation on quasi-metric relative political content preferences. Voting Party work or membership Unconventional participation ß S.E. Sig. ß S.E. Sig. ß S.E. Sig. Intercept 0,872 0,105-3,399 0,102-1,523 0,164 Relative political content preference 1,100 0,050 ** 1,423 0,075 ** 0,937 0,046 ** Number of observations Number of countries Loglikelihood 43397, , 1 ** P < 0,01, * p < 0,05 (two-tailed) 43209, Controlling for individuals backgrounds In the second model (table 16) the control variables were included. All control variables showed patterns and significances similar to the model with media content preference dummy variables (table 8). Therefore the relations of dummy variables to the dependent participation variables are not discussed here. The most important thing to notice is that the political content preference measure remained significant after the inclusion of the control variables, for all modes of political participation. This findings supports hypothesis H1a that the higher people s preferences for political media content are, the more likely they are to engage in political participation Political participation across different media environments The contextual characteristics that were included in model 3 (table 17) showed the same significant associations as the regression models with dummy content preference variables (table 11). Broadband internet penetration rates were positively associated with all modes of political participation, meaning that people living in countries with higher broadband penetration rates were more likely to engage in any kind of political participation. The total number of television channels was negatively related to party work or membership and public broadcasting audience shares were positively related to unconventional participation. So far, the same results have been found for regression models with different measures of media content preferences. 62

63 Table 16. Model 2: unstandardised logistic regression parameter estimates of voting, party work or membership and unconventional political participation on quasi-metric relative political content preferences controlled for education, gender, age, employment status, marital status, income, ethnic minority and city size. Voting Party work or membership Unconventional participation ß S.E. Sig. ß S.E. Sig. ß S.E. Sig. Intercept 1,636 0,129-3,473 0,136-1,229 0,178 Relative political content preference (RPCP) 0,673 0,052 ** 1,115 0,080 ** 0,810 0,049 ** Education (ref = 4. upper tier secondary) 1. Less than lower secondary -0,552 0,050 ** -0,541 0,090 ** -0,861 0,056 ** 2. Lower secondary -0,475 0,041 ** -0,321 0,078 ** -0,495 0,045 ** 3. Lower tier upper secondary -0,354 0,043 ** -0,278 0,079 ** -0,255 0,043 ** 5. Advanced vocational 0,137 0,046 ** 0,039 0,076 0,147 0,044 ** 6. Lower tertiary education 0,392 0,055 ** 0,331 0,076 ** 0,402 0,046 ** 7. Higher tertiary education 0,451 0,051 ** 0,398 0,072 ** 0,492 0,044 ** Gender (ref=female) -0,097 0,026 ** 0,506 0,044 ** -0,058 0,026 ** Age 0,239 0,013 ** 0,133 0,021 ** -0,084 0,013 ** Age² -0,043 0,005 ** 0,009 0,008-0,045 0,005 ** Employment status (ref = employed) Unemployed -0,356 0,046 ** -0,138 0,101-0,009 0,053 Retired 0,119 0,048 ** -0,027 0,075 0,075 0,047 Other -0,065 0,037 * -0,005 0,071 0,109 0,038 ** Marital status (ref = married) Civil union -0,686 0,120 ** -0,393 0,248 0,224 0,117 * Separated -0,354 0,133 ** 0,148 0,233-0,005 0,135 Divorced -0,493 0,044 ** -0,028 0,079 0,091 0,044 ** Widowed -0,395 0,048 ** -0,210 0,087 ** -0,079 0,055 Never married -0,285 0,037 ** -0,023 0,064 0,118 0,036 ** Income (ref = 5th decile) 1st decile -0,210 0,061 ** 0,024 0,111-0,248 0,065 ** 63

64 Table 16. continued Voting Party work or membership Unconventional participation ß S.E. Sig ß S.E. Sig ß S.E. Sig 2nd decile -0,057 0,060-0,087 0,106-0,192 0,061 ** 3rd decile -0,085 0,061-0,016 0,103-0,166 0,060 ** 4th decile -0,064 0,061-0,032 0,102-0,026 0,058 6th decile 0,111 0,064 * 0,094 0,100 0,007 0,058 7th decile 0,143 0,065 ** 0,096 0,100 0,066 0,058 8th decile 0,121 0,067 * 0,021 0,104 0,079 0,059 9th decile 0,122 0,072 * 0,028 0,108 0,038 0,062 10th decile 0,183 0,074 ** 0,303 0,101 ** 0,039 0,062 Missing income -0,067 0,053-0,028 0,089-0,179 0,051 ** Ethnic minority (ref=no) -0,751 0,036 ** -0,261 0,072 ** -0,192 0,039 ** City size (ref = 3. town or small city) 1. Farm or home in country side 0,163 0,064 ** 0,500 0,084 ** 0,041 0, Country village 0,167 0,033 ** 0,032 0,055-0,205 0,033 ** 4. Suburbs 0,022 0,045-0,085 0,075 0,178 0,042 ** 5. A big city -0,082 0,035 ** -0,182 0,063 ** 0,168 0,036 ** Number of observations Number of countries loglikelihood 40384, , ,5 ** P <.01, * p <.05 (two-tailed) Source: ESS(2010) 64

65 Table 17. Model 3: unstandardised logistic regression parameter estimates of voting, party work or membership and unconventional political participation on quasi-metric relative political content preferences and contextual media environment characteristics. 16 Voting Party work or membership Unconventional participation ß S.E. Sig ß S.E. Sig ß S.E. Sig Intercept 1,606 0,116-3,500 0,130-1,264 0,120 Relative political content preference (RPCP) 0,671 0,052 ** 1,109 0,080 ** 0,809 0,049 ** Contextual level Broadband penetration rate 0,015 0,007 ** 0,012 0,005 ** 0,030 0,007 ** Total number of television channels -0,001 0,001-0,001 0,001 * 0,001 0,001 Public broadcasting audience share 0,012 0,009 0,001 0,008 0,017 0,010 * Public broadcasting channels share -0,009 0,010-0,004 0,008-0,006 0,010 Number of observations Number of countries loglikelihood 40377, , ,1 ** P <.01, * p <.05 (two-tailed) Source: ESS(2010) and EAO(2010) 16 Control variables were also included in these models but not presented here. For full table see appendix C. 65

66 4.4.4 Relative political content preferences and absolute media content availability The cross-level interactions of media environment characteristics with the relation between media content preferences and political participation were added in model 4 (table 18, 19 and 20). Two of these media environment characteristics, broadband internet penetration rates and the total number of television channels, indicated the absolute media content availability, or total amount of information provided within media environments. The expectation regarding the cross-level interaction relationships was that: H3a: The absolute amount of information that is provided within media environments, strengthens the positive relations between relative political content preferences and political participation. A significant interaction (0,007) was found for broadband internet penetration rates with the relation between relative political content preferences and voting. In other words, in countries with higher broadband internet penetration rates, the positive relationship between relative political content preferences and voting is stronger. An increase in broadband internet penetration rates of one percentage point is associated with an increase in of 0,007. The number of television channels was positively related to the association between relative political content preferences and political party work or membership (table 19). This means that the more television channels countries media environments offers, the stronger the positive relationship between relative political preferences and political party work or membership is. So far the empirical evidence supported hypothesis H3a. There was however, also empirical evidence refuting the hypothesis. An unexpected negative interaction of broadband internet penetration with the relationship between relative political content preferences and unconventional political participation was found (table 20). This means that the positive association between relative political content preferences and unconventional political participation was weaker in countries with higher rates of broadband internet penetration Relative political content preferences and relative political content availability Public broadcasting audience and channel shares indicated the relative political content availability within media-environments. Interactions of these country-level characteristics with the relationships between relative political media content preferences and different modes of political participation were also presented in tables 18, 19 and 20. For these measures of relative political content availability positive interactions were expected: H3b: The relative amount of political information within media environments, strengthens the positive relations between relative political content preferences and political participation. 66

67 The empirical evidence (tables 18, 19 and 20) weakly supported this hypothesis. For voting a positive interaction (0,008) of public broadcasting audience shares with the relationship between relative political content preferences and voting was found. In countries with higher rates of political information supply, the positive association between political content preferences and voting is stronger. This also means that the difference in voting probabilities between people with a preference for entertainment and people with a preference for political content decreases with the increasing public broadcasting audience shares. To demonstrate this, consider this fictitious example: In country A, public broadcasting audience shares are exactly at the average level (31,4%) and in country B public broadcasting audience shares are 50% higher (81,4%). The differences in probabilities to vote between people with a preference for only entertainment (RPCP=0) and people with a preference for only politics (RPCP=1) within these two countries is calculated as follows: Country A: RPCP(0): = 1,596; 0,83 RPCP(1): = 1, *0,686; 0,91 Difference =0,08 Country B: RPCP(0): = 1, *0,008; 0,88 RPCP(1): = 1, *0, * 0,008; 0,94 Difference = 0,06 67

68 Table 18. Model 4: Unstandardised logistic regression parameter estimates of voting on quasi-metric media content preferences and contextual-level, media environment characteristics and cross-level interaction terms. 17 Model 4 - Voting ß S.E. Sig ß S.E. Sig ß S.E. Sig ß S.E. Sig Intercept 1,596 0,116 1,607 0,116 1,603 0,116 1,604 0,116 Relative political content preference (RPCP) 0,686 0,052 ** 0,671 0,052 ** 0,676 0,052 ** 0,671 0,052 ** Contextual level Broadband penetration rate 0,013 0,007 * 0,015 0,007 ** 0,015 0,007 ** 0,015 0,007 ** Total number of television channels -0,001 0,001-0,001 0,001-0,001 0,001-0,001 0,001 Public broadcasting audience shares 0,012 0,009 0,012 0,009 0,009 0,010 0,012 0,009 Public broadcasting channels shares -0,009 0,010-0,009 0,010-0,009 0,010-0,011 0,010 Crosslevel interactions Broadband penetration rate * RPCP 0,007 0,003 ** Total number of TV channels * RPCP 0,000 0,000 Public broadcasting audience shares * RPCP 0,008 0,005 * Public broadcasting channels shares * RPCP 0,004 0,004 Number of observations Number of countries loglikelihood ** P <.01, * p <.05 (two-tailed) Source: ESS(2010) and EAO(2010) 17 Control variables were also included in these models but not presented here. For full table see appendix C. 68

69 Table 19. Model 4: Unstandardised logistic regression parameter estimates of party work or membership on quasi-metric media content preferences and contextual-level, media environment characteristics and cross-level interaction terms. 18 Model 4 - Party work or membership ß S.E. Sig ß S.E. Sig ß S.E. Sig ß S.E. Sig Intercept -3,499 0,130-3,505 0,130-3,500 0,130-3,500 0,130 Relative political content preference (RPCP) 1,103 0,080 ** 1,124 0,080 ** 1,106 0,080 ** 1,102 0,080 ** Contextual level Broadband penetration rate 0,011 0,006 * 0,012 0,005 ** 0,012 0,005 ** 0,012 0,005 ** Total number of television channels -0,001 0,001-0,002 0,001 ** -0,001 0,001 * -0,001 0,001 * Public broadcasting audience share 0,001 0,008 0,001 0,008-0,001 0,008 0,000 0,008 Public broadcasting channels share -0,004 0,008-0,004 0,008-0,004 0,008-0,006 0,008 Crosslevel interactions Broadband penetration rate * RPCP 0,003 0,004 Total number of TV channels * RPCP 0,001 0,001 * Public broadcasting audience shares * RPCP 0,004 0,006 Public broadcasting channels shares * RPCP 0,004 0,005 Number of observations Number of countries loglikelihood ** P <.01, * p <.05 (two-tailed) Source: ESS(2010) and EAO(2010) 18 Control variables were also included in these models but not presented here. For full table see appendix C. 69

70 Table 20. Model 4: Unstandardised logistic regression parameter estimates of unconventional political participation on quasi-metric media content preferences and contextual-level, media environment characteristics and cross-level interaction terms. 19 Model 4 - Unconventional participation ß S.E. Sig ß S.E. Sig ß S.E. Sig ß S.E. Sig Intercept -1,270 0,120-1,261 0,119-1,266 0,120-1,264 0,120 Relative political content preference (RPCP) 0,829 0,050 ** 0,805 0,049 ** 0,817 0,050 ** 0,808 0,049 ** Contextual level Broadband penetration rate 0,033 0,007 ** 0,030 0,007 ** 0,030 0,007 ** 0,030 0,007 ** Total number of television channels 0,001 0,001 0,001 0,001 0,001 0,001 0,001 0,001 Public broadcasting audience share 0,018 0,010 * 0,017 0,010 * 0,019 0,010 * 0,017 0,010 * Public broadcasting channels share -0,006 0,010-0,006 0,010-0,006 0,010-0,006 0,011 Crosslevel interactions Broadband penetration rate * RPCP -0,005 0,003 * Total number of TV channels * RPCP 0,000 0,000 Public broadcasting audience shares * RPCP -0,004 0,004 Public broadcasting channels shares * RPCP 0,001 0,003 Number of observations Number of countries loglikelihood ** P <.01, * p <.05 (two-tailed) Source: ESS(2010) and EAO(2010) 19 Control variables were also included in these models but not presented here. For full table see appendix C. 70

71 4.4.6 Summary of the results The analyses with a quasi-metric measure of relative political media content preferences did not add much insights to the results of the analyses with media content preference dummy variables. An overview of the hypotheses and the corresponding empirical evidence is presented in table 21. The evidence showed a simplified picture of how relative content preferences, absolute and relative media content supplies and political participation are related. Relative political content preferences were positively associated to all modes of political participation. The relationships between socioeconomic and demographic background characteristics and the different modes of political participation were not affected by the use of a quasi-metric content preference measure. At the country-level, broadband internet penetration rates were found to be positively related to all modes of political participation. The number of television channels was negatively associated with political party work or membership and public broadcasting audience shares were positively associated with unconventional political participation. The advantage of using a quasi-metric measure of relative political media content preferences over dummy variables, was that it simplified the relationships and interpretability of the cross-level interactions. With regard to the cross-level interactions of the absolute media content availability indicators, mixed evidence was found. The relationships between relative political content preferences and conventional modes of political participation were positively related to the absolute availability of media contents. For unconventional political participation this association was negative. For the new country-level measure of relative political content availability, one significant association with the relation between relative political content preferences and political participation was found. In countries with higher public broadcasting audience shares, the positive relationship between voting and relative political content preferences was stronger. The use of a quasi-metric relative political media content preference measure, did not alter the results much, nor the conclusions regarding the hypotheses. In general the evidence regarding the effect of the media environment correspond. However, surprising was the finding that the relationship between relative political content preferences and unconventional political participation was negatively associated with broadband internet penetration rates. The analyses with dummy media content preferences (table 13) showed no negative associations. 71

72 Table 21. Overview of hypotheses and empirical evidence from analyses with quasi-metric relative political content preference variable. Hypotheses: Relative media content preferences H1a: The higher peoples relative preference for political media content, the more likely they are to engage in political participation. H1b: The associations between relative media content preferences and political participation vary across media types. 20 The media environment H2a: The absolute amount of information that is provided within media environments, does not affect political participation. H2b: The relative amount of political information that is supplied within media environments, positively affects political participation. Interactions of the media environment with media content preferences H3a: The absolute amount of information that is provided within media environments, strengthens the positive relations between relative political content preferences and political participation. H3b: The relative amount of political information within media environments, strengthens the positive relations between relative political content preferences Conventional political participation Party Voting work/membership Unconventional political participation (+) (+) (+) (+/0) (+/-) (+) (0) (0) (+/0) (+/0) (+/0) (-/0) (+/0) (0) (0) and political participation. *0=no empirical evidence; + = only evidence supporting hypothesis; - = only evidence refuting hypothesis; +/- = conflicting empirical evidence; +/0 = weak support for hypothesis; -/0 = weak evidence refuting hypothesis. 20 Hypothesis H1b was not tested with the quasi-metric RPCP variable due to its high amount of missing values. 72

73 Chapter 5 Conclusion In this research, the role of media content preferences and media environments in explaining political participation, has been investigated across 25 European countries using multilevel analyses. This study was inspired by Prior (2005), who explained political knowledge and participation gaps in the United States by people s relative media content preferences. He found that political knowledge and participation gaps were not rooted in people s ability to understand politics, but in their motivation to get informed. Increases in media choice in the United States enabled politically interested people to get better informed. People who preferred entertainment were better able to tune out of politics and became less politically knowledgeable and active. The first goal of this research was to test the generalisability of Prior s (2005) findings to a different (European) context. Many European countries showed the same seemingly paradoxical situation as Prior observed in the United States. European countries are highly developed in terms of mass communication technology but show stable levels of political participation at the same time (Linsen et al., 2014a). Therefore the European context lent itself perfectly for testing the robustness of Prior s (2005) findings. The relationship between media preferences and three modes of political participation (voting, party work or membership and unconventional participation) were analyzed with data from the European Social Survey (2010) and European Audiovisual Observatory (2010). Furthermore, these data enabled a test of some of Prior s (2005) implicit assumptions about the consistency of media content preferences. Another goal was to contribute to Prior s methodology regarding the influence of media environments, by proposing a new measure of relative media content availability. Prior (2005) was the first to propose the concept of relative entertainment preferences (REP). He argued that people have to choose between entertainment and news programs when using media. Their decision is based on their media content preferences. Prior stated that there is a tension between the preferences for entertainment and news. Because people can only consume one type of content at a time, a high preference for entertainment automatically implies a low preference for news, hence the term relative entertainment preference. He found that a relative preference for entertainment was negatively related to political participation. In this study, political media content preferences were the topic of interest. A political content preference measure was constructed by dividing the time people spent consuming political media content by the total time they spent using media. All media contents other than political content, were assumed to be entertainment. Political content preferences and their relation to different modes of political participation were analyzed across 25 European countries. The first research question read: 73

74 RQ1: To what extent are there relationships between preferences for political content (for different types of media) and political participation in European countries, over and beyond other relevant determinants? The results showed that overall political content preferences were positively related to both conventional and unconventional modes of political participation. One exception was found for voting. People with the highest political content preference were less likely to vote than people with an equal preference for entertainment and political media contents. These people might prefer unconventional ways of participation over conventional ways. The predominantly positive relationship between political content preferences and political participation appeared to be rather robust. Controlling for several other important determinants of political participation did not reduce the positive association between media content preferences and political participation. This means that Prior s (2005) claim of the influence of media preferences on political participation, is supported by European country data. The European Social Survey data contained information on user patterns for different media types, enabling the construction of media-specific content preference measures. These measures took the possibility into account that people might have different preferences for different media types and use these media differently. Analyses with the media-specific measures provided some unexpected evidence. First of all, content preferences for radio and newspapers were associated to political participation in a different way than television content preferences. For both radio and newspaper it was found that both a preference for entertainment and political content negatively affected political participation. Media content preferences for television were most strongly related to political participation and showed associations in the expected direction. Relative preferences for political content were positively related to political participation compared to people without a clear preference and people who preferred entertainment were less likely to participate politically compared to people without a clear preference. The media-specific preference measures were eventually discarded due to the large amount of missing information on the use of the different media types. Nevertheless, these findings do indicate that some media types are differently and more strongly related to political participation, than others. The European Social Survey data were lacking information on internet use. Therefore the construction of an internet content preference measure was not feasible. The development of better media-specific content preference measures should be pursued in future research. 74

75 The extent to which individuals media content preferences influence their tendency to participate politically is related to their (media) environment. According to Prior (2005) the amount of media choice people have i.e. the amount of different contents people can choose from influences the tendency of different groups of people to participate differently. He observed that in the United States political participation remained relatively stable over a given time span, where growth in mass communication technology was exponential. This paradoxical finding, he claimed, could be explained by the growth in media choice within the American media environment that affected the political participation of politically interested people positively and the participation of politically uninterested people negatively. With advances in mass communication, media choice increased, which reduced chance encounters with any political content significantly, expanding the divide between people with different content preferences. To what extent this influence of the media environment on political participation can be generalized to other contexts was not researched yet. Therefore the second research question read: RQ2: To what extent are there relationships between media environments in European countries and political participation within these countries? The European Social Survey data, enriched with data from the European Audiovisual Observatory, enabled the exploration of the relationship between characteristics of media environments and political participation. According to Prior (2005), media choice within media environments interacts with the effect of individual content preferences on political participation. In other words, people who prefer political content will participate more in politics when they are offered more media content by their media environments. They will have more political content to choose from, hence consume more political content instead of entertainment, become more politically knowledgeable and become more likely to participate in politics. People with a preference for entertainment will have more entertainment options and will therefore consume more entertainment. In a low-choice environment, Prior claimed, these people are incidentally exposed to political information, every now and then. The lack of entertainment alternatives makes people sit through the news. These chance encounters decrease with an increasing media choice. Deduced from this was that media choice offered by media environments, does not affect political participation directly. After all, political participation was found to be stable, while mass communication and with it, media choice, were expanding. Only when interacted with media content preferences diverging effects for people with different preferences were expected and found (Prior, 2005). During the process of data collection it became clear that previous research had missed a crucial aspect of media choice within media environments. Measures for media choice used in previous research (Prior, 2005; 2007; Rittenberg et al., 2012) were broadband internet access and 75

76 cable television access. Having access to cable television instead of terrestrial television was said to increase media choice, because this type of television offered more channels. Broadband internet compared to slower types of internet, generated more choice because the transmission of data was higher. Therefore more web content could be downloaded within the same amount of time. Although these assumptions are plausible, the media choice people have always depends on the media content they are offered. This aspect is not accounted for by measures like cable TV or broadband internet access. The media content that is offered has changed drastically in Europe over the past decades. Europe went through a transition from an era of public service domination to a multichannel environment commanded by commercial providers, since the mid 1980s. Cable networks and satellite became key features and television flourished as a commodity selling industry. Gradually commercial broadcasters began to dominate the television landscape with a strong emphasis on entertainment (Wieten et al., 2000). Wieten et al. expected that in the future entertainment programming will continue to increase. If the extra channels that cable TV offer predominantly broadcast entertainment, to what extent is there an increase in choice? It is crucial know what kind of contents are provided by the extra channels that were made available by cable television. Therefore, cable TV access alone might not be a valid indicator for media choice across Europe. In this research an alternative approach to media environments was proposed. Next to measures that indicated the absolute amount of information provided with media environments, an alternative media choice measure was introduced. This measure was assumed to indicate the political information to entertainment ratio among the contents that were supplied by media environments. Two different types of media environment characteristics were analyzed. The first type of media environment characteristics was called the absolute media content supply. This supply was operationalised by broadband internet penetration rates and number of available television channels. If countries scored higher on these measures it was assumed that these countries and their media environments offered their citizens more media content. What type of content they offer was left aside. These measures were not sufficient to make inferences about the kind of media content that was supplied. Having access to cable television does not necessarily imply an exposure to media content that enables one to get informed about current affairs. There must also be a supply of news programs that provide political information in order to gain political knowledge. Therefore a second type of media environment characteristics was proposed in this study, which was referred to as relative media content supply. In contrast to the measures of absolute media content supply -that do not distinguish between entertainment or political content -, these new relative measurements were indications of the relative amounts of political contents that are supplied within media environments. Because it was impossible to label all the information on the internet as either 76

77 entertainment or political content, only the medium television was used to construct the relative content supply measures. Countries channel and audience shares of public broadcasters were used as a measure of political information supply. Watching public broadcasting channels had been associated with the consumption of more hard news and therefore more knowledge of current affairs which is positively related to political participation. It was assumed that countries with higher shares of public broadcasting, had higher supplies of political media contents. The results regarding the direct influences of the two different types of media environment measures were unexpected. The absolute media content supply (broadband internet penetration rates) was positively associated with all modes of political participation. This means that there is an effect of broadband internet on political participation, regardless of individual s media content preferences. The relative supply of political media content was expected to have a direct positive effect on political participation, but a positive relationship was only found for unconventional participation. As mentioned in the past few paragraphs, the relation between a preference for political media content and political participation was expected to be related to the media choice, or media content supply within media environments. Prior (2005) interacted the concept of media choice with media content preferences to explain the stable overall levels of political participation in the United States. European countries showed the same paradoxical situation of stable political participation levels and fast expanding mass communication technology. This research set out to test the influence of media choice in the European context. Therefore the final research question read: RQ3: To what extent do the relations between preferences for political content and political participation, vary over European countries with different levels of media choice? The different measures used to capture aspects of media choice within media environments had diverging relationships with the associations between content preferences and different modes of political participation. The overview of the hypotheses and empirical evidence (table 14) showed that there is some support for nearly every hypothesis, but also empirical evidence rejecting them. The measures of absolute media content supply, showed only weak associations with media content preferences. Only the relation between a preference for political media content and political party work or membership was strengthened by absolute media content supply by media environments. The negative relationship between a preference for entertainment and conventional political participation was in some cases weakened and in others strengthened by the absolute media content supplies. For both voting and unconventional participation, the analyses showed conflicting evidence. The number of television channels within countries strengthened the negative association, whereas broadband internet penetration rates weakened the negative relationship 77

78 between entertainment preferences and unconventional political participation. The negative association between entertainment preferences and voting was strengthened by broadband internet penetration rates and weakened by the number of television channels. The new measures of relative media content supply, provided some mixed results as well. The positive association between a preference for political media content and conventional political participation was strengthened by countries relative political content supply. The relationship between political content preferences and unconventional participation was not affected. A less clear interaction of the relative supply of political contents with the relationship between preferences for entertainment content and political participation was observed. The negative relation between a preference for entertainment and voting was strengthened by the relative supply of political media contents. No effects were found for political party work of membership. The negative relationship between a preference for entertainment and unconventional political participation was weakened by public broadcasting channel shares and strengthened by public broadcasting audience shares. The results provided no clear answer to the third research question. Conflicting evidence and complex relationships of the country-level media environment characteristics with the associations between media content preferences and different modes of political participation, complicated the formulation of a clear answer. To clarify the relationships between the media environment, individual media content preferences and political participation, additional analyses were conducted with a quasi-metric content preference measure (tables 15-20). The results showed that the measures of absolute media content supply (broadband internet penetration and number of television channels) were positively related to the association between relative political content preferences and voting. This means that in European countries with higher absolute supplies of media content, media content preferences are stronger predictors of voting than in countries with lower supplies. The difference in the probabilities to vote between people with a preference for entertainment and people with a preference for politics is greater if the absolute media content supply is higher. This is in accordance with Prior s (2005) findings that changes in a media environment affect the political participation of people with different content preferences differently. For party work or membership a positive interaction for only one of the indicators (number of television channels) was found. The difference in probabilities to do party work or be a party member, between people who preferred entertainment and people who preferred politics, was larger in countries with a higher number of television channels. Probabilities to participate unconventionally were more equally distributed among people with different media content preferences in countries with higher rates of broadband internet penetration rates. Only one significant interaction was found for the relative political content supply by media 78

79 environments. Public broadcasting audience shares were positively associated with the relationship between relative political content preferences and voting. This means that the relationship between media content preferences and voting is stronger in countries with higher public broadcasting shares. The difference in probabilities to vote between people with a preference for entertainment and people with a preference for politics, on the other hand, is smaller in countries with higher public broadcasting shares. Greater relative supplies of political information within media environments close the voting gap between people with different media content preferences. The relative share of political information seems to decrease voter inequality. The general conclusion is that political media content preferences positively affect all modes of political participation in Europe. This relationship is affected by European countries media environments. The absolute supply of information by media environments widened the voting gap between people with a preference for entertainment and people with a preference for political media content. This finding is in accordance with Prior s (2005) findings for the United States. On the contrary, the unconventional political participation gap between the two preference groups closed with an increasing supply of information by media environments. The newly proposed relative political information measure did not affect the relationship between media content prefences and political participation in the expected way. The relative supply of political information increased instead of closed the voting gap between people with different media content preferences. 79

80 80

81 Chapter 6 Discussion This research contributed to the research on media content preferences and the media environment in several ways. First of all, Prior s (2005) hypotheses on the interplay between relative media content preferences, media choice and political participation were tested in a European context. Secondly, alternative operationalisations of media content preferences and media choice within media environments were proposed in this study, which painted a more nuanced picture of the relationships between preferences, choice and participation. The use of multilevel logistic regression analysis enabled the analysis of contextual-level media environment effects. The influence of the media environment could therefore be estimated separately from individual-level effects. In this thesis media content preferences measures were constructed that were different from Prior s (2005). The original relative entertainment preference measures were based on a ranking of favorite television genres. This ranking was assumed to indicate peoples general preferences for either entertainment or politics for all media, also for internet content. The preference measures in this study were based on self-reported media use. People were asked how much time they spent using television, radio and newspapers and how much of that time was spent on news or programs about current affairs. These questions were combined to construct a single preference measure for television, radio and newspaper. This measure has an advantage over the original REP measure, because it was not based on the assumption that people s favorite television program ranking indicates their content preferences for other media. Furthermore, reported media use indicates behavior, which is a direct expression of media preferences. This study indicated that different types of political participation are affected differently by media preferences and different aspects of the media environment. The analyses also indicated that the relationships between media content preferences and different modes of political participation are not consistent across different media types. This finding deserves more attention in future research. Furthermore the significant associations of the public broadcasting measures suggested that the concept of relative political media content supply, is a valuable contribution to the existing literature regarding the interplay between media content preferences, choice within the media environment and political participation. Although previous research has linked public broadcasting to higher levels of political knowledge (Soroka et al., 2013; Curran et al., 2009), it had not yet been linked to the theoretical concept of media choice within media environments and its effects on political participation. The finding that broadband internet penetration affects political participation directly, above and beyond the effects of individual content preferences and internet access is interesting. It suggests that the picture painted by Prior (2005), that stable political participation levels over time 81

82 are actually hiding two diverging participation trends for people with different media content preferences which level each other out, might be too simplistic for Europe. Overall participation rates were positively affected by the relatively new medium broadband internet, over and beyond the effects of individual media preferences, but still these participation rates were stable over time. This suggests that advances in communication technology, such as broadband internet, might compensate for a downward trend in political participation. A possible explanation might be that internet can be a means of political participation that is replacing traditional ways of political participation. It might also be related to countries levels of prosperity. Linsen et al. (2014b) found that countries prosperity induced unconventional political participation. Developments in mass communication technology are highest in more prosperous countries. Broadband internet penetration rates are therefore likely to be strongly related to countries prosperity levels. Instead of being an effect of information availability, the broadband internet effect might actually reflect a prosperity effect. Unfortunately there were some drawbacks to this research. First of all, the media-specific preference measures which were supposed to be valuable additions to the existing media preference literature, suffered from a high amount of missing values. This was the reason that a general media content preferences measure for television, radio and newspaper combined, was analyzed. The regression analysis with media-specific content preference dummy variables (table 8b, appendix B) did however indicate, that the relationship between media content preferences and political participation varies across different media types. The general media content preference regression coefficients are largely determined by people s television content preferences. Furthermore the data only provided limited information on internet use, which is one of the most important media in the 21 st century. Since country-level broadband internet penetration rates were analyzed, it would have been nice to have a measure indicating internet content preferences. Now it is assumed that content preferences for television, radio and newspaper reflect preferences for internet content. Another limitation of this research was that there was no direct measure available for the supply of political information within media environments. Public broadcasting audience and channels shares were used as proxies for the supply of political information. Compared to commercial television channels, public broadcasting channels supply more hard news (Aalberg et al., 2010). A higher share of public broadcasting channels within countries was therefore assumed to indicate higher relative political information supplies. First of all, it is questionable to what extent audience market shares reflect the supply of political information within a media environment. There shares predominantly reflect the demand for public broadcasting television content among the television audience and not the actual information supply. Furthermore, the measure might be biased and not very comparable across countries. Public broadcasters also broadcast entertainment 82

83 programs and broadcasters political information to entertainment ratio s are unknown. The validity of public broadcasting channel and audience shares as measures of political information supplies is therefore in question. This does not mean that the concept of a relative political information supply should be discarded as a whole. Because it seems a theoretically strong claim that the politics to entertainment ratio in media content supply matters, rejecting the hypothesis would be premature. In this study a first attempt is made to distinguish between absolute information supply and the relative supply of political information within the absolute supply of information. The challenge for future research lies in improving the operationalisation of the relative supply of political media content. In hindsight the second hypothesis (H2a) is questionable. Because Prior (2005) only predicted an interaction effect of media choice with the relation between media preferences and political participation, the hypothesis was deduced that there would be no direct effect of media choice on political participation. After all, political participation rates were stable over time during times of increasing mass communication technology. However, it might be the case that the developments in communication technology do have a positive effect and are compensating a downward trend in participation. Despite the drawbacks of this study, some support for Prior s (2005; 2007) conditional political learning (CPL) model was found in Europe. Strong evidence was found that preferences for political media content positively affect political participation. As expected, broadband internet increased the gap between people with a preference for entertainment and those who prefer political content. The limited empirical support regarding the other media environment characteristics might be partly due to weak operationalisations or to the fact that European media environments are different from the United States media environment. Another explanation for the fact that Prior found stronger effects from the media environment might be that he did not apply multilevel analysis. He assumed to capture media environment effects by taking individual-level media access into account. In my opinion this does not really capture actual media choice that media users have, because it does not account for the contents that are supplied by the medium one has access to. Much improvement can be made in future research by using multi-level analysis and by developing the concepts of the media environment and media choice and their operationalisations. Another aspect that I wish I could have elaborated more is accidental exposure to political media content. Prior (2005) assumed that this affected the political knowledge of people back in the days when there was not much media choice. The accidental exposure to news for people with entertainment preferences decreased over time with the increasing media choice and widened the political knowledge and participation gap between people with different preferences. The effect of accidental media exposure on political participation has not been accounted for in this research. 83

84 The finding that people with a preference for political media content are more likely to participate than people with a preference for entertainment is not very surprising, because these preferences are probably strongly related to general political interest. More interesting would be to know to what extent accidental news exposure nowadays affects political participation of people with different media preferences. 84

85 A: Descriptive statistics and full regression tables Table 1. Descriptive statistics of individual-level variables. N Min Max Mean S.D. Dependent variables Conventional political participation Voting ,77 0,42 Party membership or work ,06 0,24 Unconventional Political Participation ,26 0,44 Independent variables Relative Political Content Preference (RPCP) ,39 0,26 RPCP Television Only entertainment ,07 0,25 Mostly entertainment ,52 0,50 Equal preference ,14 0,35 Mostly politics ,11 0,31 Only politics ,13 0,34 Missing preference ,04 0,19 RPCP Radio Only entertainment ,13 0,34 Mostly entertainment ,34 0,47 Equal preference ,04 0,20 Mostly politics ,04 0,21 Only politics ,17 0,38 Missing preference ,27 0,45 RPCP Newspaper Only entertainment ,09 0,29 Mostly entertainment ,19 0,39 Equal preference ,02 0,13 Mostly politics ,04 0,19 Only politics ,32 0,47 Missing preference ,34 0,47 85

86 Table 1. continued. Control variables Education ,77 1,86 Sex (0=male, 1 female) ,46 0,50 Age ,50 17,67 Employment status employed ,49 0,50 unemployed ,07 0,26 retired ,29 0,45 other ,15 0,36 Marital status married ,53 0,50 civil union ,01 0,10 separated ,01 0,09 divorced ,09 0,29 widowed ,11 0,31 never married ,25 0,43 Income 1st decile ,09 0,29 2nd decile ,09 0,29 3rd decile ,08 0,28 4th decile ,08 0,27 5th decile ,08 0,28 6th decile ,08 0,27 7th decile ,08 0,27 8th decile ,07 0,25 9th decile ,06 0,23 10th decile ,06 0,24 income missing ,22 0,42 Ethnic minority (0=no, 1=yes) ,11 0,32 City size ,88 1,24 Political interest ,66 0,92 Valid N (listwise) Source: ESS(2010) 86

87 Table 2. Descriptive statistics of voting per country. N Min Max Mean S.D. Belgium ,88 0,32 Bulgaria ,78 0,42 Switzerland ,64 0,48 Cyprus ,85 0,36 Czech Republic ,63 0,48 Germany ,82 0,39 Denmark ,92 0,27 Estonia ,72 0,45 Spain ,83 0,37 Finland ,84 0,37 France ,72 0,45 United Kingdom ,73 0,45 Greece ,79 0,41 Croatia ,75 0,43 Hungary ,73 0,44 Ireland ,71 0,45 Lithuania ,62 0,49 Netherlands ,83 0,37 Norway ,87 0,33 Poland ,74 0,44 Portugal ,75 0,43 Russian Federation ,69 0,46 Sweden ,94 0,24 Slovenia ,72 0,45 Slovakia ,74 0,44 Source: ESS(2010) 87

88 Table 3. Descriptive statistics of party membership or work per country. Country N Min Max Mean S.D. Belgium ,08 0,28 Bulgaria ,06 0,23 Switzerland ,11 0,31 Cyprus ,13 0,33 Czech Republic ,04 0,20 Germany ,05 0,23 Denmark ,09 0,28 Estonia ,06 0,24 Spain ,08 0,28 Finland ,09 0,29 France ,04 0,21 United Kingdom ,03 0,18 Greece ,06 0,24 Croatia ,10 0,30 Hungary ,03 0,17 Ireland ,05 0,22 Lithuania ,04 0,20 Netherlands ,07 0,26 Norway ,11 0,31 Poland ,02 0,15 Portugal ,03 0,17 Russian Federation ,06 0,23 Sweden ,09 0,29 Slovenia ,05 0,23 Slovakia ,02 0,15 Source: ESS(2010) 88

89 Table 4. Descriptive statistics of party membership or work per country. Country N Min Max Mean S.D. Belgium ,26 0,44 Bulgaria ,09 0,29 Switzerland ,50 0,50 Cyprus ,12 0,32 Czech Republic ,22 0,41 Germany ,47 0,50 Denmark ,44 0,50 Estonia ,16 0,37 Spain ,37 0,48 Finland ,48 0,50 France ,49 0,50 United Kingdom ,37 0,48 Greece ,18 0,39 Croatia ,26 0,44 Hungary ,09 0,29 Ireland ,19 0,39 Lithuania ,11 0,32 Netherlands ,31 0,46 Norway ,48 0,50 Poland ,13 0,34 Portugal ,09 0,28 Russian Federation ,09 0,29 Sweden ,54 0,50 Slovenia ,13 0,34 Slovakia ,23 0,42 Source: ESS(2010) Table 5. Descriptive statistics of contextual-level characteristics. N Min Max Mean S.D. Broadband internet penetration rate 25 7,20 82,00 49,96 17,84 Total number of television channels ,20 129,55 Public channel share of total channels (terrestrial and cable) 25 2,56 62,96 16,34 13,95 TV Audience market share public channels (2009) 25 12,80 66,50 31,44 12,59 Source: EAO(2010) 89

90 Table 6. Cramér s phi association matrix of the single and media-specific RPCP measures. RPCP RPCP television RPCP radio RPCP newspaper RPCP 1 0,578* 0,343* 0,236* RPCP television 0,578* 1 0,142* 0,128* RPCP radio 0,343* 0,142* 1 0,136* RPCP newspaper 0,236* 0,128* 0,136* 1 * p <.05 N = Source: ESS(2010) 88

91 Table 10. Model 3: Unstandardised regression parameter estimates of voting, party work or membership and unconventional participation on contextuallevel media environment characteristics (full table). Voting Party work or membership Unconventional participation ß S.E. Sig. ß S.E. Sig. ß S.E. Sig. Intercept 2,043 0,118-2,825 0,130-0,742 0,120 Relative content preference (ref = 3. equal preference) 1. Only entertainment -0,901 0,058 ** -0,846 0,151 ** -0,689 0,073 ** 2. Mostly entertainment -0,255 0,035 ** -0,421 0,054 ** -0,333 0,032 ** 4. Mostly politics 0,086 0,048 * 0,146 0,061 ** 0,034 0, Only politics -0,244 0,059 ** 0,280 0,079 ** 0,134 0,053 ** Missing preference -0,995 0,131 ** -0,650 0,344 * -0,507 0,185 ** Education (ref = 4. upper tier secondary) 1. Less than lower secondary -0,531 0,050 ** -0,547 0,090 ** -0,870 0,056 ** 2. Lower secondary -0,464 0,041 ** -0,331 0,078 ** -0,500 0,045 ** 3. Lower tier upper secondary -0,367 0,043 ** -0,293 0,079 ** -0,266 0,042 ** 5. Advanced vocational 0,120 0,046 ** 0,029 0,076 0,140 0,043 ** 6. Lower tertiary education 0,390 0,055 ** 0,333 0,076 ** 0,404 0,046 ** 7. Higher tertiary education 0,462 0,051 ** 0,397 0,072 ** 0,496 0,044 ** Gender (ref=female) -0,100 0,026 ** 0,508 0,044 ** -0,054 0,026 ** Age 0,231 0,013 ** 0,131 0,021 ** -0,084 0,013 ** Age² -0,041 0,005 ** 0,010 0,008-0,045 0,005 ** Employment status (ref = employed) Unemployed -0,348 0,046 ** -0,133 0,100-0,007 0,053 Retired 0,113 0,048 ** -0,032 0,074 0,068 0,047 Other -0,059 0,037-0,009 0,071 0,112 0,038 ** Marital status (ref = married) Civil union -0,710 0,119 ** -0,407 0,248 0,207 0,117 * Separated -0,305 0,133 ** 0,126 0,233-0,025 0,135 Divorced -0,489 0,044 ** -0,019 0,079 0,100 0,044 ** Widowed -0,404 0,048 ** -0,212 0,087 ** -0,076 0,055 Never married -0,291 0,037 ** -0,035 0,064 0,111 0,036 ** Income (ref = 5th decile) 1st decile -0,180 0,061 ** 0,027 0,111-0,239 0,065 ** 89

92 2nd decile -0,044 0,060-0,083 0,106-0,192 0,061 ** 3rd decile -0,078 0,061-0,018 0,103-0,166 0,060 ** 4th decile -0,056 0,061-0,029 0,102-0,024 0,058 6th decile 0,112 0,063 * 0,085 0,100 0,002 0,058 7th decile 0,136 0,065 ** 0,086 0,100 0,061 0,057 8th decile 0,118 0,067 * 0,011 0,104 0,073 0,059 9th decile 0,099 0,072 0,010 0,108 0,027 0,062 10th decile 0,178 0,074 ** 0,300 0,101 ** 0,040 0,062 Missing income -0,055 0,053-0,019 0,089-0,183 0,051 ** Ethnic minority (ref=no) -0,738 0,036 ** -0,251 0,072 ** -0,189 0,039 ** City size (ref = 3. town or small city) 1. Farm or home in country side 0,133 0,063 ** 0,480 0,084 ** 0,036 0, Country village 0,169 0,032 ** 0,034 0,055-0,204 0,033 ** 4. Suburbs 0,020 0,045-0,088 0,074 0,174 0,042 ** 5. A big city -0,073 0,035 ** -0,176 0,063 ** 0,175 0,036 ** Contextual-level Broadband penetration rate 0,015 0,007 ** 0,012 0,005 ** 0,031 0,007 ** Total number of television channels -0,001 0,001-0,001 0,001 * 0,001 0,001 Public broadcasting audience share 0,012 0,010 0,001 0,008 0,018 0,010 * Public broadcasting channels share -0,009 0,010-0,004 0,008-0,006 0,010 Number of observations Number of countries loglikelihood 40634, ,4 ** P <.01, * p <.05 (two-tailed) Sources: ESS(2010) and EAO(2010) 90

93 Table 11. Model 4: Unstandardised regression parameters of voting on contextual-level media environment characteristics and cross-level interaction terms (full table). Model 4 - Voting ß S.E. Sig. ß S.E. Sig. ß S.E. Sig. ß S.E. Sig. Intercept 2,048 0,120 2,078 0,131 2,072 0,125 2,067 0,129 Relative content preference (ref = 3. equal preference) 1. Only entertainment -0,932 0,060 ** -0,910 0,058 ** -0,912 0,059 ** -0,946 0,059 ** 2. Mostly entertainment -0,259 0,035 ** -0,256 0,035 ** -0,257 0,035 ** -0,256 0,035 ** 4. Mostly politics 0,082 0,048 * 0,087 0,048 * 0,087 0,048 * 0,082 0,048 * 5. Only politics -0,240 0,059 ** -0,243 0,059 ** -0,244 0,059 ** -0,242 0,059 ** Missing preference -0,984 0,132 ** -0,996 0,131 ** -0,998 0,131 ** -0,991 0,131 ** Education (ref = 4. upper tier secondary) 1. Less than lower secondary -0,530 0,050 ** -0,533 0,050 ** -0,533 0,050 ** -0,535 0,050 ** 2. Lower secondary -0,462 0,041 ** -0,463 0,041 ** -0,464 0,041 ** -0,464 0,041 ** 3. Lower tier upper secondary -0,365 0,043 ** -0,364 0,043 ** -0,364 0,043 ** -0,365 0,043 ** 5. Advanced vocational 0,121 0,046 ** 0,121 0,046 ** 0,120 0,046 ** 0,122 0,046 ** 6. Lower tertiary education 0,386 0,055 ** 0,391 0,055 ** 0,389 0,055 ** 0,389 0,055 ** 7. Higher tertiary education 0,460 0,051 ** 0,462 0,051 ** 0,461 0,051 ** 0,462 0,051 ** Gender (ref=female) -0,099 0,026 ** -0,100 0,026 ** -0,099 0,026 ** -0,098 0,026 ** Age 0,231 0,013 ** 0,231 0,013 ** 0,231 0,013 ** 0,231 0,013 ** Age² -0,041 0,005 ** -0,041 0,005 ** -0,041 0,005 ** -0,041 0,005 ** Employment status (ref = employed) Unemployed -0,350 0,046 ** -0,351 0,046 ** -0,351 0,046 ** -0,350 0,046 ** Retired 0,114 0,048 ** 0,112 0,048 ** 0,112 0,048 ** 0,115 0,048 ** Other -0,059 0,037-0,061 0,037-0,059 0,037-0,059 0,037 Marital status (ref = married) Civil union -0,711 0,119 ** -0,708 0,119 ** -0,708 0,119 ** -0,709 0,119 ** Separated -0,302 0,133 ** -0,305 0,133 ** -0,304 0,133 ** -0,302 0,134 ** Divorced -0,489 0,044 ** -0,490 0,044 ** -0,490 0,044 ** -0,489 0,044 ** Widowed -0,406 0,048 ** -0,405 0,048 ** -0,405 0,048 ** -0,404 0,048 ** Never married -0,291 0,037 ** -0,290 0,037 ** -0,290 0,037 ** -0,289 0,037 ** Income (ref = 5th decile) 1st decile -0,180 0,061 ** -0,183 0,061 ** -0,181 0,061 ** -0,180 0,061 ** 2nd decile -0,042 0,060-0,044 0,060-0,044 0,060-0,043 0,060 3rd decile -0,078 0,061-0,080 0,061-0,078 0,061-0,078 0,061 91

94 4th decile -0,052 0,061-0,057 0,061-0,056 0,061-0,054 0,061 6th decile 0,112 0,063 * 0,110 0,063 * 0,112 0,063 * 0,112 0,063 * 7th decile 0,135 0,065 ** 0,137 0,065 ** 0,135 0,065 ** 0,136 0,065 ** 8th decile 0,115 0,067 * 0,116 0,067 * 0,117 0,067 * 0,119 0,067 * 9th decile 0,096 0,072 0,097 0,072 0,097 0,072 0,099 0,072 10th decile 0,176 0,074 ** 0,176 0,074 ** 0,175 0,074 ** 0,177 0,074 ** Missing income -0,053 0,053-0,057 0,053-0,056 0,053-0,055 0,053 Ethnic minority (ref=no) -0,737 0,036 ** -0,739 0,036 ** -0,737 0,036 ** -0,734 0,036 ** City size (ref = 3. town or small city) 1. Farm or home in country side 0,132 0,063 ** 0,135 0,063 ** 0,133 0,063 ** 0,129 0,064 ** 2. Country village 0,168 0,032 ** 0,169 0,032 ** 0,168 0,032 ** 0,170 0,032 ** 4. Suburbs 0,019 0,045 0,018 0,045 0,020 0,045 0,021 0, A big city -0,075 0,035 ** -0,074 0,035 ** -0,074 0,035 ** -0,074 0,035 ** Contextual level Broadband penetration rate 0,016 0,007 ** 0,015 0,007 * 0,015 0,007 * 0,015 0,007 * Total number of television channels -0,001 0,001-0,001 0,001-0,001 0,001-0,001 0,001 Public broadcasting audience share 0,011 0,010 0,012 0,010 0,011 0,010 0,011 0,010 Public broadcasting channels share -0,009 0,010-0,009 0,010-0,009 0,010-0,007 0,010 Crosslevel interactions with relative media preferences (ref=3. equal preference) 1. Only entertainment -0,006 0,003 * 0,001 0,000 * -0,003 0,005-0,024 0,006 ** 2. Mostly entertainment -0,002 0,002 0,000 0,000-0,001 0,003-0,001 0, Mostly politics 0,003 0,003 0,000 0,000 0,009 0,004 ** 0,003 0, Only politics 0,004 0,003 0,000 0,000 0,002 0,005-0,004 0,004 Number of observations Number of countries loglikelihood ** P <.01, * p <.05 (two-tailed) Sources: ESS(2010) and EAO(2010) 92

95 Table 12. Model 4: Unstandardised regression parameters of party work or membership on contextual-level media environment characteristics and crosslevel interaction terms (full table). Model 4 - Party work or membership ß S.E. Sig. ß S.E. Sig. ß S.E. Sig. ß S.E. Sig. Intercept -2,805 0,130-2,825 0,130-2,821 0,130-2,820 0,130 Relative content preference (ref = 3. equal preference) 1. Only entertainment -0,841 0,153 ** -0,845 0,152 ** -0,836 0,154 ** -0,847 0,152 ** 2. Mostly entertainment -0,446 0,055 ** -0,422 0,055 ** -0,426 0,055 ** -0,429 0,055 ** 4. Mostly politics 0,116 0,064 * 0,150 0,062 ** 0,130 0,062 ** 0,133 0,062 ** 5. Only politics 0,214 0,084 ** 0,293 0,080 ** 0,271 0,081 ** 0,253 0,081 ** Missing preference -0,729 0,345 ** -0,650 0,344 * -0,660 0,345 * -0,668 0,344 * Education (ref = 4. upper tier secondary) 1. Less than lower secondary -0,548 0,090 ** -0,545 0,090 ** -0,549 0,090 ** -0,547 0,090 ** 2. Lower secondary -0,330 0,078 ** -0,330 0,078 ** -0,331 0,078 ** -0,329 0,078 ** 3. Lower tier upper secondary -0,292 0,079 ** -0,291 0,079 ** -0,290 0,079 ** -0,290 0,079 ** 5. Advanced vocational 0,029 0,076 0,027 0,076 0,028 0,076 0,031 0, Lower tertiary education 0,333 0,076 ** 0,334 0,076 ** 0,331 0,076 ** 0,333 0,076 ** 7. Higher tertiary education 0,395 0,072 ** 0,397 0,072 ** 0,395 0,072 ** 0,397 0,072 ** Gender (ref=female) 0,509 0,044 ** 0,507 0,044 ** 0,509 0,044 ** 0,509 0,044 ** Age 0,131 0,021 ** 0,131 0,021 ** 0,131 0,021 ** 0,131 0,021 ** Age² 0,010 0,008 0,009 0,008 0,010 0,008 0,010 0,008 Employment status (ref = employed) Unemployed -0,130 0,100-0,132 0,100-0,135 0,100-0,134 0,100 Retired -0,031 0,075-0,031 0,074-0,032 0,075-0,032 0,075 Other -0,010 0,071-0,009 0,071-0,011 0,071-0,009 0,071 Marital status (ref = married) Civil union -0,400 0,248-0,408 0,248-0,407 0,248-0,405 0,248 Separated 0,135 0,233 0,127 0,233 0,127 0,233 0,129 0,233 Divorced -0,017 0,079-0,021 0,079-0,020 0,079-0,019 0,079 Widowed -0,212 0,087 ** -0,213 0,087 ** -0,213 0,087 ** -0,212 0,087 ** Never married -0,034 0,064-0,036 0,064-0,036 0,064-0,034 0,064 Income (ref = 5th decile) 1st decile 0,028 0,111 0,028 0,111 0,029 0,111 0,024 0,111 2nd decile -0,081 0,106-0,081 0,106-0,082 0,106-0,082 0,106 3rd decile -0,016 0,103-0,017 0,103-0,017 0,103-0,018 0,103 93

96 4th decile -0,024 0,102-0,027 0,102-0,028 0,102-0,027 0,102 6th decile 0,087 0,100 0,085 0,100 0,086 0,100 0,086 0,100 7th decile 0,087 0,100 0,086 0,100 0,086 0,100 0,085 0,100 8th decile 0,012 0,104 0,011 0,104 0,011 0,104 0,009 0,104 9th decile 0,013 0,108 0,010 0,108 0,011 0,108 0,010 0,108 10th decile 0,303 0,101 ** 0,300 0,101 ** 0,300 0,101 ** 0,300 0,101 ** Missing income -0,016 0,089-0,019 0,089-0,018 0,089-0,018 0,089 Ethnic minority (ref=no) -0,255 0,072 ** -0,252 0,072 ** -0,251 0,072 ** -0,252 0,072 ** City size (ref = 3. town or small city) 1. Farm or home in country side 0,480 0,084 ** 0,477 0,084 ** 0,479 0,084 ** 0,483 0,084 ** 2. Country village 0,035 0,055 0,033 0,055 0,032 0,055 0,034 0, Suburbs -0,088 0,074-0,088 0,074-0,089 0,074-0,087 0, A big city -0,177 0,063 ** -0,177 0,063 ** -0,177 0,063 ** -0,176 0,063 ** Contextual level Broadband penetration rate 0,006 0,006 0,012 0,005 ** 0,012 0,005 ** 0,012 0,005 ** Total number of television channels -0,001 0,001 * -0,001 0,001-0,001 0,001 * -0,001 0,001 * Public broadcasting audience share 0,001 0,008 0,001 0,008-0,001 0,008 0,001 0,008 Public broadcasting channels share -0,004 0,008-0,004 0,008-0,004 0,008-0,008 0,008 Crosslevel interactions with relative media preferences (ref=3. equal preference) 1. Only entertainment 0,014 0,009 0,000 0,001 0,008 0,013 0,010 0, Mostly entertainment 0,007 0,003 ** 0,000 0,000 0,000 0,004 0,003 0, Mostly politics 0,007 0,004 * 0,000 0,001 0,007 0,005 0,005 0, Only politics 0,014 0,005 ** 0,001 0,001 0,005 0,006 0,010 0,005 * Number of observations Number of countries loglikelihood ** P <.01, * p <.05 (two-tailed) Sources: ESS(2010) and EAO(2010) 94

97 Table 13. Model 4: Unstandardised regression parameters of unconventional political participation on contextual-level media environment characteristics and cross-level interaction terms (full table). Model 4 - Unconventional participation ß S.E. Sig. ß S.E. Sig. ß S.E. Sig. ß S.E. Sig. Intercept -0,726 0,121-0,743 0,120-0,740 0,120-0,736 0,120 Relative content preference (ref = 3. equal preference) 1. Only entertainment -0,705 0,073 ** -0,661 0,073 ** -0,715 0,074 ** -0,698 0,073 ** 2. Mostly entertainment -0,357 0,033 ** -0,332 0,032 ** -0,340 0,033 ** -0,338 0,032 ** 4. Mostly politics 0,037 0,043 0,034 0,040 0,044 0,041 0,027 0, Only politics 0,127 0,056 ** 0,135 0,053 ** 0,135 0,055 ** 0,125 0,054 ** Missing preference -0,534 0,184 ** -0,507 0,185 ** -0,512 0,184 ** -0,519 0,185 ** Education (ref = 4. upper tier secondary) 1. Less than lower secondary -0,870 0,056 ** -0,869 0,056 ** -0,867 0,056 ** -0,870 0,056 ** 2. Lower secondary -0,502 0,045 ** -0,499 0,045 ** -0,499 0,045 ** -0,500 0,045 ** 3. Lower tier upper secondary -0,268 0,042 ** -0,266 0,042 ** -0,267 0,042 ** -0,266 0,042 ** 5. Advanced vocational 0,140 0,043 ** 0,140 0,043 ** 0,141 0,043 ** 0,140 0,043 ** 6. Lower tertiary education 0,405 0,046 ** 0,403 0,046 ** 0,406 0,046 ** 0,404 0,046 ** 7. Higher tertiary education 0,498 0,044 ** 0,496 0,044 ** 0,499 0,044 ** 0,497 0,044 ** Gender (ref=female) -0,055 0,026 ** -0,054 0,026 ** -0,055 0,026 ** -0,054 0,026 ** Age -0,083 0,013 ** -0,084 0,013 ** -0,084 0,013 ** -0,084 0,013 ** Age² -0,045 0,005 ** -0,045 0,005 ** -0,045 0,005 ** -0,045 0,005 ** Employment status (ref = employed) Unemployed -0,004 0,053-0,008 0,053-0,006 0,053-0,007 0,053 Retired 0,068 0,047 0,068 0,047 0,069 0,047 0,068 0,047 Other 0,114 0,038 ** 0,113 0,038 ** 0,114 0,038 ** 0,112 0,038 ** Marital status (ref = married) Civil union 0,207 0,117 * 0,206 0,117 * 0,208 0,117 * 0,207 0,117 * Separated -0,024 0,135-0,024 0,135-0,024 0,135-0,024 0,135 Divorced 0,101 0,044 ** 0,100 0,044 ** 0,101 0,044 ** 0,100 0,044 ** Widowed -0,076 0,055-0,076 0,055-0,076 0,055-0,075 0,055 Never married 0,112 0,036 ** 0,112 0,036 ** 0,112 0,036 ** 0,111 0,036 ** Income (ref = 5th decile) 1st decile -0,240 0,065 ** -0,240 0,065 ** -0,241 0,065 ** -0,240 0,065 ** 2nd decile -0,193 0,061 ** -0,193 0,061 ** -0,192 0,061 ** -0,192 0,061 ** 3rd decile -0,164 0,060 ** -0,166 0,060 ** -0,166 0,060 ** -0,165 0,060 ** 95

98 4th decile -0,024 0,058-0,024 0,058-0,023 0,058-0,023 0,058 6th decile 0,003 0,058 0,002 0,058 0,002 0,058 0,002 0,058 7th decile 0,062 0,057 0,060 0,057 0,060 0,057 0,060 0,057 8th decile 0,075 0,059 0,073 0,059 0,073 0,059 0,072 0,059 9th decile 0,031 0,062 0,027 0,062 0,028 0,062 0,028 0,062 10th decile 0,042 0,062 0,038 0,062 0,039 0,062 0,039 0,062 Missing income -0,183 0,051 ** -0,183 0,051 ** -0,182 0,051 ** -0,183 0,051 ** Ethnic minority (ref=no) -0,189 0,039 ** -0,189 0,039 ** -0,188 0,039 ** -0,189 0,039 ** City size (ref = 3. town or small city) 1. Farm or home in country side 0,035 0,055 0,037 0,055 0,036 0,055 0,036 0, Country village -0,204 0,033 ** -0,205 0,033 ** -0,204 0,033 ** -0,205 0,033 ** 4. Suburbs 0,175 0,042 ** 0,175 0,042 ** 0,175 0,042 ** 0,174 0,042 ** 5. A big city 0,176 0,036 ** 0,175 0,036 ** 0,174 0,036 ** 0,174 0,036 ** Contextual level Broadband penetration rate 0,028 0,007 ** 0,031 0,007 ** 0,031 0,007 ** 0,031 0,007 ** Total number of television channels 0,001 0,001 0,002 0,001 0,001 0,001 0,001 0,001 Public broadcasting audience share 0,018 0,010 * 0,018 0,010 * 0,016 0,010 0,018 0,010 * Public broadcasting channels share -0,006 0,010-0,006 0,010-0,006 0,010-0,009 0,011 Crosslevel interactions with relative media preferences (ref=3. equal preference) 1. Only entertainment -0,001 0,004-0,001 0,000 ** -0,011 0,007 * 0,001 0, Mostly entertainment 0,005 0,002 ** 0,000 0,000 0,004 0,003 0,004 0,002 * 4. Mostly politics 0,000 0,003 0,000 0,000-0,003 0,003 0,004 0, Only politics 0,001 0,003-0,001 0,000 0,000 0,004 0,004 0,003 Number of observations Number of countries loglikelihood ** P <.01, * p <.05 (two-tailed) Sources: ESS(2010) and EAO(2010) 96

99 Appendix B: Additional models Table 8b. Unstandardised regression parameter estimates of voting, party work or membership and unconventional political participation on relative political content preferences, controlled for political interest. Vote Party work or membership Unconventional participation ß S.E. Sig. ß S.E. Sig. ß S.E. Sig. Intercept 2,040 0,128-3,164 0,143-0,798 0,174 RPCP (ref = 3. equal preference) 1. Only entertainment -0,447 0,061 ** 0,007 0,157-0,262 0,075 ** 2. Mostly entertainment -0,108 0,036 ** -0,188 0,056 ** -0,209 0,033 ** 4. Mostly politics 0,015 0,049 0,004 0,063-0,039 0, Only politics -0,216 0,060 ** 0,229 0,082 ** 0,128 0,054 ** Missing preference -0,650 0,133 ** 0,005 0,353-0,191 0,188 Education (ref = 4. upper tier secondary) 1. Less than lower secondary -0,296 0,051 ** -0,183 0,092 ** -0,677 0,057 ** 2. Lower secondary -0,345 0,042 ** -0,143 0,079 * -0,395 0,046 ** 3. Lower tier upper secondary -0,281 0,044 ** -0,152 0,081 * -0,188 0,043 ** 5. Advanced vocational 0,113 0,047 ** -0,001 0,077 ** 0,133 0,044 ** 6. Lower tertiary education 0,295 0,056 ** 0,183 0,077 ** 0,330 0,046 ** 7. Higher tertiary education 0,347 0,052 ** 0,178 0,073 ** 0,387 0,045 ** Gender (ref=female) -0,207 0,027 ** 0,323 0,045 ** -0,153 0,026 ** Age 0,208 0,013 ** 0,069 0,021 ** -0,118 0,013 ** Age² -0,037 0,005 ** 0,018 0,008 ** -0,042 0,005 ** Employment status (ref = employed) Unemployed -0,353 0,047 ** -0,123 0,102-0,009 0,054 Retired 0,057 0,049-0,105 0,075 0,022 0,047 Other -0,094 0,038 ** -0,057 0,073 0,085 0,038 ** Marital status (ref = married) Civil union -0,704 0,121 ** -0,344 0,252 0,240 0,118 ** Separated -0,300 0,135 ** 0,152 0,238-0,029 0,138 Divorced -0,479 0,044 ** -0,007 0,080 0,110 0,045 ** Widowed -0,398 0,049 ** -0,185 0,089 ** -0,057 0,056 Never married -0,287 0,037 ** -0,025 0,066 0,118 0,037 ** Income (ref = 5th decile) 97

100 1st decile -0,151 0,062 ** 0,063 0,114-0,213 0,066 ** 2nd decile -0,018 0,061-0,055 0,108-0,173 0,062 ** 3rd decile -0,054 0,062 0,015 0,105-0,151 0,061 ** 4th decile -0,061 0,062-0,035 0,104-0,031 0,059 6th decile 0,085 0,065 0,054 0,102-0,019 0,058 7th decile 0,123 0,066 0,068 0,102 0,043 0,058 8th decile 0,096 0,068-0,032 0,106 0,042 0,060 9th decile 0,060 0,073-0,079 0,110-0,025 0,063 10th decile 0,105 0,075 0,199 0,103 * -0,026 0,063 Missing income -0,029 0,054 0,021 0,091-0,170 0,052 Ethnic minority (ref=no) -0,757 0,037 ** -0,273 0,074 ** -0,187 0,039 ** City size (ref = 3. town or small city) 1. Farm or home in country side 0,140 0,064 ** 0,531 0,086 ** 0,043 0, Country village 0,197 0,033 ** 0,072 0,056-0,191 0,033 ** 4. Suburbs 0,017 0,046-0,108 0,076 0,171 0,042 ** 5. A big city -0,096 0,036 ** -0,244 0,064 ** 0,146 0,036 ** Political interest -0,524 0,016 ** -0,936 0,029 ** -0,463 0,016 ** Number of observations Number of countries loglikelihood 39387, , ,4 ** P < 0,01, * p < 0,05 (two-tailed) Source: EAO(2010) 98

101 Table 9. Unstandardised regression parameter estimates of aggregated broadband penetration rates on the total number of television channels, public broadcasting audience shares and public broadcasting channel shares. A test for multicollinearity among country-level characteristics. Broadband internet penetration ß S.E. Sig. Beta Tolerance VIF Intercept 30,888 8,887 Total number of television channels 0,045 0,031 0,300 0,774 1,291 Public broadcasting audience shares 0,161 0,307 0,114 0,711 1,407 Public broadcasting channel shares 0,627 0,294 * 0,490 0,633 1,581 Number of observations 25 R² 0,298 ** P < 0,01, * p < 0,05 (two-tailed) Source: EAO(2010) 99

102 Appendix C: Regression models with quasi-metric media content preference measures Table 17. Model 3: unstandardised regression parameter estimates of voting, party work or membership and unconventional political participation on quasimetric relative political content preferences and contextual media environment characteristics (full table). Voting Party work or membership Unconventional participation ß S.E. Sig. ß S.E. Sig. ß S.E. Sig. Intercept 1,606 0,116-3,500 0,130-1,264 0,120 Relative political content preference (RPCP) 0,671 0,052 ** 1,109 0,080 ** 0,809 0,049 ** Education (ref = 4. upper tier secondary) 1. Less than lower secondary -0,552 0,050 ** -0,539 0,090 ** -0,862 0,056 ** 2. Lower secondary -0,476 0,041 ** -0,324 0,078 ** -0,497 0,045 ** 3. Lower tier upper secondary -0,356 0,043 ** -0,285 0,080 ** -0,256 0,043 ** 5. Advanced vocational 0,135 0,046 ** 0,038 0,076 0,146 0,044 ** 6. Lower tertiary education 0,391 0,055 ** 0,328 0,076 ** 0,400 0,046 ** 7. Higher tertiary education 0,451 0,051 ** 0,398 0,072 ** 0,492 0,044 ** Gender (ref=female) -0,097 0,026 ** 0,506 0,044 ** -0,058 0,026 ** Age 0,239 0,013 ** 0,132 0,021 ** -0,084 0,013 ** Age² -0,043 0,005 ** 0,009 0,008-0,045 0,005 ** Employment status (ref = employed) Unemployed -0,355 0,046 ** -0,137 0,101-0,008 0,053 Retired 0,119 0,048 ** -0,026 0,075 0,076 0,047 Other -0,065 0,037 * -0,006 0,071 0,109 0,038 ** Marital status (ref = married) Civil union -0,687 0,120 ** -0,396 0,248 0,222 0,117 * Separated -0,355 0,133 ** 0,144 0,233-0,007 0,135 Divorced -0,494 0,044 ** -0,028 0,079 0,091 0,044 ** Widowed -0,394 0,048 ** -0,207 0,087 ** -0,078 0,055 Never married -0,286 0,037 ** -0,027 0,064 0,118 0,036 ** Income (ref = 5th decile) 1st decile -0,208 0,061 ** 0,028 0,111-0,248 0,066 ** 2nd decile -0,056 0,060-0,083 0,106-0,193 0,061 ** 3rd decile -0,084 0,061-0,014 0,103-0,166 0,060 ** 4th decile -0,064 0,061-0,031 0,102-0,026 0,

103 6th decile 0,111 0,064 * 0,093 0,100 0,007 0,058 7th decile 0,142 0,065 ** 0,094 0,100 0,066 0,058 8th decile 0,121 0,067 * 0,020 0,104 0,079 0,059 9th decile 0,121 0,072 * 0,026 0,108 0,038 0,062 10th decile 0,183 0,074 ** 0,300 0,101 ** 0,038 0,062 Missing income -0,066 0,053-0,026 0,089-0,179 0,051 ** Ethnic minority (ref=no) -0,753 0,036 ** -0,264 0,072 ** -0,193 0,039 ** City size (ref = 3. town or small city) 1. Farm or home in country side 0,160 0,064 ** 0,490 0,084 ** 0,039 0, Country village 0,167 0,033 ** 0,030 0,055-0,205 0,033 ** 4. Suburbs 0,021 0,045-0,088 0,075 0,176 0,042 ** 5. A big city -0,081 0,035 ** -0,179 0,063 ** 0,170 0,036 ** Contextual level Broadband penetration rate 0,015 0,007 ** 0,012 0,005 ** 0,030 0,007 ** Total number of television channels -0,001 0,001-0,001 0,001 * 0,001 0,001 Public broadcasting audience share 0,012 0,009 0,001 0,008 0,017 0,010 * Public broadcasting channels share -0,009 0,010-0,004 0,008-0,006 0,010 Number of observations Number of countries loglikelihood 40377, , ,1 ** P <.01, * p <.05 (two-tailed) Sources: ESS(2010) and EAO(2010) 101

104 Table 18. Model 4: Unstandardised regression parameter estimates of voting on quasi-metric media content preferences and contextual-level, media environment characteristics and cross-level interaction terms (full table). Model 4 - Voting ß S.E. Sig. ß S.E. Sig. ß S.E. Sig. ß S.E. Sig. Intercept 1,596 0,116 1,607 0,116 1,603 0,116 1,604 0,116 Relative political content preference (RPCP) 0,686 0,052 ** 0,671 0,052 ** 0,676 0,052 ** 0,671 0,052 ** Education (ref = 4. upper tier secondary) 1. Less than lower secondary -0,551 0,050 ** -0,550 0,050 ** -0,552 0,050 ** -0,553 0,050 ** 2. Lower secondary -0,474 0,041 ** -0,475 0,041 ** -0,475 0,041 ** -0,476 0,041 ** 3. Lower tier upper secondary -0,355 0,043 ** -0,356 0,043 ** -0,355 0,043 ** -0,356 0,043 ** 5. Advanced vocational 0,135 0,046 ** 0,135 0,046 ** 0,136 0,046 ** 0,136 0,046 ** 6. Lower tertiary education 0,389 0,055 ** 0,391 0,055 ** 0,391 0,055 ** 0,391 0,055 ** 7. Higher tertiary education 0,450 0,051 ** 0,451 0,051 ** 0,451 0,051 ** 0,451 0,051 ** Gender (ref=female) -0,097 0,026 ** -0,097 0,026 ** -0,097 0,026 ** -0,096 0,026 ** Age 0,238 0,013 ** 0,239 0,013 ** 0,239 0,013 ** 0,239 0,013 ** Age² -0,043 0,005 ** -0,043 0,005 ** -0,043 0,005 ** -0,043 0,005 ** Employment status (ref = employed) Unemployed -0,357 0,046 ** -0,355 0,046 ** -0,357 0,046 ** -0,356 0,046 ** Retired 0,120 0,048 ** 0,119 0,048 ** 0,120 0,048 ** 0,120 0,048 ** Other -0,065 0,037 * -0,065 0,037 * -0,065 0,037 * -0,064 0,037 * Marital status (ref = married) Civil union -0,687 0,120 ** -0,688 0,120 ** -0,685 0,120 ** -0,686 0,120 ** Separated -0,352 0,133 ** -0,354 0,133 ** -0,355 0,133 ** -0,355 0,133 ** Divorced -0,493 0,044 ** -0,494 0,044 ** -0,494 0,044 ** -0,493 0,044 ** Widowed -0,395 0,048 ** -0,395 0,048 ** -0,394 0,048 ** -0,394 0,048 ** Never married -0,286 0,037 ** -0,286 0,037 ** -0,286 0,037 ** -0,286 0,037 ** Income (ref = 5th decile) 1st decile -0,208 0,061 ** -0,207 0,061-0,208 0,061-0,209 0,061 2nd decile -0,055 0,060-0,056 0,060-0,057 0,060-0,057 0,060 3rd decile -0,084 0,061-0,084 0,061-0,084 0,061-0,085 0,061 4th decile -0,061 0,061-0,064 0,061-0,064 0,061-0,064 0,061 6th decile 0,111 0,064 * 0,111 0,064 * 0,111 0,064 * 0,111 0,064 * 7th decile 0,141 0,065 ** 0,142 0,065 ** 0,142 0,065 ** 0,142 0,065 ** 8th decile 0,119 0,067 * 0,120 0,067 * 0,120 0,067 * 0,121 0,067 * 9th decile 0,118 0,072 0,120 0,072 * 0,120 0,072 * 0,121 0,072 * 102

105 10th decile 0,180 0,074 ** 0,182 0,074 ** 0,182 0,074 ** 0,183 0,074 ** Missing income -0,065 0,053-0,066 0,053-0,066 0,053-0,065 0,053 Ethnic minority (ref=no) -0,753 0,036 ** -0,754 0,036 ** -0,753 0,036 ** -0,753 0,036 ** City size (ref = 3. town or small city) 1. Farm or home in country side 0,160 0,064 ** 0,158 0,064 ** 0,160 0,064 ** 0,162 0,064 ** 2. Country village 0,166 0,033 ** 0,166 0,033 ** 0,166 0,033 ** 0,167 0,033 ** 4. Suburbs 0,021 0,045 0,021 0,045 0,021 0,045 0,022 0, A big city -0,083 0,035 ** -0,081 0,035 ** -0,081 0,035 ** -0,080 0,035 ** Contextual level Broadband penetration rate 0,013 0,007 * 0,015 0,007 ** 0,015 0,007 ** 0,015 0,007 ** Total number of television channels -0,001 0,001-0,001 0,001-0,001 0,001-0,001 0,001 Public broadcasting audience shares 0,012 0,009 0,012 0,009 0,009 0,010 0,012 0,009 Public broadcasting channels shares -0,009 0,010-0,009 0,010-0,009 0,010-0,011 0,010 Crosslevel interactions Broadband penetration rate * RPCP 0,007 0,003 ** Total number of TV channels * RPCP 0,000 0,000 Public broadcasting audience shares * RPCP 0,008 0,005 * Public broadcasting channels shares * RPCP 0,004 0,004 Number of observations Number of countries loglikelihood ** P <.01, * p <.05 (two-tailed) Sources: ESS(2010) and EAO(2010) 103

106 Table 19. Model 4: Unstandardised regression parameter estimates of party work or membership on quasi-metric media content preferences, contextuallevel media environment characteristics and cross-level interaction terms (full table). Model 4 - Party work or membership ß S.E. Sig. ß S.E. Sig. ß S.E. Sig. ß S.E. Sig. Intercept -3,499 0,130-3,505 0,130-3,500 0,130-3,500 0,130 Relative political content preference (RPCP) 1,103 0,080 ** 1,124 0,080 ** 1,106 0,080 ** 1,102 0,080 ** Education (ref = 4. upper tier secondary) 1. Less than lower secondary -0,538 0,090 ** -0,535 0,090 ** -0,539 0,090 ** -0,540 0,090 ** 2. Lower secondary -0,323 0,078 ** -0,323 0,078 ** -0,324 0,078 ** -0,324 0,078 ** 3. Lower tier upper secondary -0,283 0,080 ** -0,283 0,080 ** -0,283 0,080 ** -0,283 0,080 ** 5. Advanced vocational 0,038 0,076 0,037 0,076 0,039 0,076 0,039 0, Lower tertiary education 0,327 0,076 ** 0,329 0,076 ** 0,328 0,076 ** 0,327 0,076 ** 7. Higher tertiary education 0,397 0,072 ** 0,398 0,072 ** 0,398 0,072 ** 0,398 0,072 ** Gender (ref=female) 0,507 0,044 ** 0,505 0,044 ** 0,507 0,044 ** 0,508 0,044 ** Age 0,132 0,021 ** 0,132 0,021 ** 0,132 0,021 ** 0,132 0,021 ** Age² 0,009 0,008 0,009 0,008 0,009 0,008 0,009 0,008 Employment status (ref = employed) Unemployed -0,138 0,101-0,137 0,101-0,138 0,101-0,139 0,101 Retired -0,026 0,075-0,026 0,075-0,026 0,075-0,026 0,075 Other -0,007 0,071-0,007 0,071-0,007 0,071-0,006 0,071 Marital status (ref = married) Civil union -0,395 0,248-0,399 0,248-0,395 0,248-0,394 0,248 Separated 0,146 0,233 0,144 0,233 0,144 0,233 0,146 0,233 Divorced -0,028 0,079-0,031 0,079-0,029 0,079-0,028 0,079 Widowed -0,207 0,087 ** -0,208 0,087 ** -0,207 0,087 ** -0,206 0,087 ** Never married -0,027 0,064-0,028 0,064-0,027 0,064-0,026 0,064 Income (ref = 5th decile) 1st decile 0,028 0,111 0,030 0,111 0,029 0,111 0,028 0,111 2nd decile -0,083 0,106-0,081 0,106-0,083 0,106-0,083 0,106 3rd decile -0,014 0,103-0,013 0,103-0,014 0,103-0,014 0,103 4th decile -0,030 0,102-0,030 0,102-0,031 0,102-0,031 0,102 6th decile 0,093 0,100 0,092 0,100 0,093 0,100 0,093 0,100 7th decile 0,094 0,100 0,094 0,100 0,094 0,100 0,094 0,100 8th decile 0,019 0,104 0,019 0,104 0,020 0,104 0,019 0,104 9th decile 0,025 0,108 0,024 0,108 0,026 0,108 0,026 0,

107 10th decile 0,300 0,101 ** 0,299 0,101 ** 0,301 0,101 ** 0,301 0,101 ** Missing income -0,026 0,089-0,027 0,089-0,026 0,089-0,026 0,089 Ethnic minority (ref=no) -0,264 0,072 ** -0,266 0,072 ** -0,264 0,072 ** -0,264 0,072 ** City size (ref = 3. town or small city) 1. Farm or home in country side 0,491 0,084 ** 0,486 0,084 ** 0,490 0,084 ** 0,492 0,084 ** 2. Country village 0,030 0,055 0,029 0,055 0,030 0,055 0,031 0, Suburbs -0,088 0,075-0,088 0,075-0,088 0,075-0,088 0, A big city -0,180 0,063 ** -0,180 0,063 ** -0,179 0,063 ** -0,179 0,063 ** Contextual level Broadband penetration rate 0,011 0,006 * 0,012 0,005 ** 0,012 0,005 ** 0,012 0,005 ** Total number of television channels -0,001 0,001-0,002 0,001 ** -0,001 0,001 * -0,001 0,001 * Public broadcasting audience share 0,001 0,008 0,001 0,008-0,001 0,008 0,000 0,008 Public broadcasting channels share -0,004 0,008-0,004 0,008-0,004 0,008-0,006 0,008 Crosslevel interactions Broadband penetration rate * RPCP 0,003 0,004 Total number of TV channels * RPCP 0,001 0,001 * Public broadcasting audience shares * RPCP 0,004 0,006 Public broadcasting channels shares * RPCP 0,004 0,005 Number of observations Number of countries loglikelihood ** P <.01, * p <.05 (two-tailed) Sources: ESS(2010) and EAO(2010) 105

108 Table 20. Model 4: Unstandardised regression parameter estimates of unconventional participation on quasi-metric media content preferences, contextuallevel media environment characteristics and cross-level interaction terms (full table). Model 4 - Unconventional participation ß S.E. Sig. ß S.E. Sig. ß S.E. Sig. ß S.E. Sig. Intercept -1,270 0,120-1,261 0,119-1,266 0,120-1,264 0,120 Relative political content preference 0,829 0,050 ** 0,805 0,049 ** 0,817 0,050 ** 0,808 0,049 ** Education (ref = 4. upper tier secondary) 1. Less than lower secondary -0,863 0,056 ** -0,861 0,056 ** -0,862 0,056 ** -0,862 0,056 ** 2. Lower secondary -0,499 0,045 ** -0,496 0,045 ** -0,498 0,045 ** -0,497 0,045 ** 3. Lower tier upper secondary -0,258 0,043 ** -0,255 0,043 ** -0,257 0,043 ** -0,256 0,043 ** 5. Advanced vocational 0,146 0,044 ** 0,146 0,044 ** 0,146 0,044 ** 0,146 0,044 ** 6. Lower tertiary education 0,401 0,046 ** 0,400 0,046 ** 0,400 0,046 ** 0,400 0,046 ** 7. Higher tertiary education 0,493 0,044 ** 0,492 0,044 ** 0,492 0,044 ** 0,492 0,044 ** Gender (ref=female) -0,059 0,026 ** -0,059 0,026 ** -0,059 0,026 ** -0,058 0,026 ** Age -0,083 0,013 ** -0,084 0,013 ** -0,084 0,013 ** -0,084 0,013 ** Age² -0,045 0,005 ** -0,045 0,005 ** -0,045 0,005 ** -0,045 0,005 ** Employment status (ref = employed) Unemployed -0,006 0,053-0,008 0,053-0,007 0,053-0,009 0,053 Retired 0,075 0,047 0,076 0,047 0,076 0,047 0,076 0,047 Other 0,110 0,038 ** 0,109 0,038 ** 0,109 0,038 ** 0,109 0,038 ** Marital status (ref = married) Civil union 0,220 0,117 * 0,221 0,117 * 0,220 0,117 * 0,222 0,117 * Separated -0,010 0,135-0,007 0,135-0,007 0,135-0,007 0,135 Divorced 0,091 0,044 ** 0,090 0,044 ** 0,091 0,044 ** 0,091 0,044 ** Widowed -0,078 0,055-0,078 0,055-0,078 0,055-0,078 0,055 Never married 0,118 0,036 ** 0,118 0,036 ** 0,118 0,036 ** 0,118 0,036 ** Income (ref = 5th decile) 1st decile -0,249 0,065 ** -0,247 0,066 ** -0,249 0,066 ** -0,248 0,066 ** 2nd decile -0,194 0,061 ** -0,192 0,061 ** -0,193 0,061 ** -0,193 0,061 ** 3rd decile -0,166 0,060 ** -0,166 0,060 ** -0,166 0,060 ** -0,166 0,060 ** 4th decile -0,028 0,058-0,026 0,058-0,026 0,058-0,026 0,058 6th decile 0,007 0,058 0,007 0,058 0,007 0,058 0,007 0,058 7th decile 0,066 0,058 0,066 0,058 0,066 0,058 0,066 0,058 8th decile 0,080 0,059 0,079 0,059 0,079 0,059 0,079 0,059 9th decile 0,040 0,062 0,038 0,062 0,039 0,062 0,038 0,062 10th decile 0,039 0,062 0,038 0,062 0,038 0,062 0,038 0,

109 Missing income -0,180 0,051 ** -0,180 0,051 ** -0,179 0,051 ** -0,179 0,051 ** Ethnic minority (ref=no) -0,193 0,039 ** -0,194 0,039 ** -0,193 0,039 ** -0,193 0,039 ** City size (ref = 3. town or small city) 1. Farm or home in country side 0,039 0,055 0,038 0,055 0,040 0,055 0,040 0, Country village -0,205 0,033 ** -0,206 0,033 ** -0,204 0,033 ** -0,205 0,033 ** 4. Suburbs 0,177 0,042 ** 0,176 0,042 ** 0,177 0,042 ** 0,176 0,042 ** 5. A big city 0,171 0,036 ** 0,170 0,036 ** 0,170 0,036 ** 0,170 0,036 ** Contextual level Broadband penetration rate 0,033 0,007 ** 0,030 0,007 ** 0,030 0,007 ** 0,030 0,007 ** Total number of television channels 0,001 0,001 0,001 0,001 0,001 0,001 0,001 0,001 Public broadcasting audience share 0,018 0,010 * 0,017 0,010 * 0,019 0,010 * 0,017 0,010 * Public broadcasting channels share -0,006 0,010-0,006 0,010-0,006 0,010-0,006 0,011 Crosslevel interactions Broadband penetration rate * RPCP -0,005 0,003 * Total number of TV channels * RPCP 0,000 0,000 Public broadcasting audience shares * RPCP -0,004 0,004 Public broadcasting channels shares * RPCP 0,001 0,003 Number of observations Number of countries loglikelihood ** P <.01, * p <.05 (two-tailed) Sources: ESS(2010) and EAO(2010) 107

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113 Notes i The EAO yearbook did not classify British and Russian TV channels as being either public or private. Public broadcasting classifications for these countries were derived from the book Western broadcast models by d Haenens and Saeys (2007). The British BBC channels are considered public, while ITV, Channel 4 and Channel 5 are considered private (d Haenen & Saeys, 2007, p.334). Channels in the Russian Federation which are considered public are: Pervyj Kanal, Rossija (also includes: Kultura, Sport and Vesti), TV-Center and ZVEZDA. Private channels in the Russian Federation are NTV, TNT, REN TV and CTC(STS) (d Haenens & Saeys, 2007, p ). 111