Education sector: Working conditions and job quality

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1 European Foundation for the Improvement of Living and Working Conditions sector: Working conditions and job quaity Work pays a significant roe in peope s ives, in the functioning of companies and in society at arge. But what is work? How can we describe it? Is it changing, and if so, is it for better or for worse? Is it fufiing the numerous and at times conficting expectations we have of it? How can we take steps to improve work for the we-being of a? Eurofound, Fifth European Working Conditions Survey: Overview report, 2012 This report gives an overview of working conditions, job quaity, workers heath and job sustainabiity in the education sector (NACE 85). 1 It is based mosty on the fifth European Working Conditions Survey (EWCS), which gathers data on working conditions and the quaity of work across 34 European countries. Additiona information on the structura characteristics of the sector is derived from Eurostat data. The sector incudes a educationa activities: pre-primary, primary, secondary and higher education, as we as other educationa activities and educationa support activities. The fifth EWCS contains responses from 3,157 workers in this sector. The report compares aspects of work in the sector with the as a whoe. Structura characteristics In 2010, 16,031,900 European workers worked in the education sector, 7.4% of the workforce (Eurostat, 2013). Empoyment in the sector increased by 3.4 percentage points between 2008 and 2010, and by a further 0.5 percentage points between 2010 and 2012 (Eurostat, 2013). Countries where the education sector is a reativey arge empoyer are Latvia (where it empoys 10.4% of the workforce), the United Kingdom (10.6%), Sweden (10.8%) and Lithuania (11.6%). The sector has ess prominence in Bugaria (empoying 6. of the workforce), the Czech Repubic (6.), Croatia (5.9%) and Romania (4.2%) (Eurostat, 2013). A arge proportion of workers in education (74.) work in sma and medium-sized workpaces ( ), compared to 46% in the. Consequenty, workers in micro-workpaces (1 9 ) and arge workpaces (250 and over), where they make up 2 and 7% 1 Nomencature statistique des activités économiques dans a Communauté européenne (statistica cassification of economic activities in the European Community). respectivey of the workforce, are reativey underrepresented in the sector in comparison to the, where the figures are 42% and 12% respectivey. The sector is femae-dominated: 72% of workers are women and 28% are men (Eurostat, 2013). Young workers (beow 25 years of age) and workers aged between 25 and 39 are reativey underrepresented in the sector, as they make up 5% and 34% respectivey of the sector s workforce, compared to 9% and 36% in the as a whoe. On the other hand, oder workers (50 years and over) make up a arger-thanaverage proportion of the workforce (33% compared to 27% in the ). Indefinite contracts are the predominant form of empoyment in education (81% of the workforce), but fixed-term contracts are more common in the sector (14%) than in the (12%) (Figure 1). Working without a forma contract, on the other hand, is ess common than in the. Part-time work is consideraby more prevaent in the education sector than in the, with 56% of women and 4 of men in the sector working 34 sector in a nutshe The sector is femae-dominated Amost one-third of women working in microworkpaces woud prefer to work more hours Workers receive a high eve of empoyer-paid training A reativey arge proportion of workers report being under-skied Earnings are ower when compared with earnings of workers with simiar profies in other sectors Leves of job strain are reativey ow Presenteeism (working when sick) in the sector shoud be addressed 1

2 Figure 1: Empoyment status, by gender Tota Indefinite contract Temporary agency contract No contract Fixed-term contract Apprenticeship or other training scheme Other hours or ess, compared to 38% of women and 13% of men in the. Sef-empoyment is not very prevaent, with ony 4% reporting they are sefempoyed without and 1% reporting they are sef-empoyed with, compared to 11% and 4% respectivey in the. Working conditions Changes since the crisis Figure 2 shows that workers in the education sector were more ikey to report changes in their working hours in the year prior to the survey than workers in the as a whoe. Across a workpace sizes, the proportion of workers reporting no changes to their working hours was ower than in equivaent workpaces in the, whie the proportion of workers reporting an increase in working hours was higher than in the equivaent workpaces. Workers in micro-workpaces were most affected by working hours reductions, with 15% reporting decreased working time, whie workers in arge workpaces were most ikey to have experienced an increase in their working hours (reported by 39% of the workforce in arge workpaces). Both in the education sector and in the in genera, workers more frequenty reported changes in saary or income than changes in hours worked in the year prior to the survey. Empoyees in microworkpaces more frequenty reported wage cuts than those in sma and medium-sized workpaces and arge workpaces. Across a workpace sizes, however, the proportion of reporting a decrease in saary is smaer than the proportion reporting an increase, and smaer than in the equivaent workpaces. Conversey, across a workpace sizes in education, the proportion of reporting an increase in saary (26% in Figure 2: Percentage of reporting changes in number of hours worked and saary or income in past year, by workpace size Change in number of hours worked Change in saary or income Decrease No change Increase

3 7 6 micro-workpaces, 35% in sma and medium-sized workpaces and 5 in arge workpaces) is higher than in the equivaent workpaces (21%, 29% and 37% respectivey). Workers in education were sighty more ikey to report the introduction of new technoogies and processes in the three years prior to the survey than workers in the as a whoe. Overa, the sector does not differ from the average in the reported incidence of restructuring and reorganisation (Figure 3). The education sector foows the same pattern as the : the share of reporting restructuring or reorganisation or the introduction of new production processes and technoogies increases with workpace size. Figure 3: Restructuring and introduction of new technoogies in past three years, by workpace size However, the share of reported changes (for both new technoogies and restructuring) in the sector was arger than in the for micro-workpaces, but smaer for sma and medium-sized workpaces. Workers in arge workpaces in education were more ikey to report changes in technoogy and processes but ess ikey to report restructuring or reorganisation than their counterparts. Working time and work ife baance Workers in education work 31 hours on average per week, compared to 38 hours in the. As in the, men in the education sector tend to work more hours than women, independent of workpace size (Figure 4). In education, both women and men empoyed in arge workpaces report the highest working hours. Whie women s average working hours increase proportionay in reation to workpace size, for men they are highest in arge workpaces and owest in sma and medium-sized workpaces. Figure 4: Average working hours, by gender New technoogies and processes introduced Tota Tota Substantia restructuring or reorganisation Figure 5: Working time preferences, by gender and workpace size Tota Tota Less than currenty Same as currenty More than currenty 3

4 The preferences of workers in education with regard to their working time do not differ much from those of workers in the as a whoe. Overa, 57% of workers in education say they woud prefer to work the same number of hours as currenty, compared to 55% in the, whie the proportion of those expressing a preference for working ess than currenty is sighty ower (28% in the sector compared to 31% in the as a whoe) Figure 7: Index of reguarity of working time, by gender and workpace size Across a workpace sizes, the proportion of workers who woud prefer to work fewer hours than currenty is higher than that of workers who woud prefer to work more hours, with the exception of women working in micro-workpaces, among whom the share of those who woud prefer to work more hours than currenty (31%) is higher than the corresponding average (19%) and aso higher than the share of those who woud prefer to decrease their working hours (2) Tota It is interesting to note that, overa, the proportion of women in the education sector who woud prefer to work more hours does not differ from the corresponding average (15%), whie that of men (16%) is higher than for the (12%). Figure 6 shows that working atypica hours (weekends, evenings or nights) is ess common in education than in the as a whoe, especiay for women. The same pattern hods across a workpace sizes in the education sector, with the exception of men working in micro-workpaces, who are more ikey to work atypica hours than the average. Figure 6: Index of working atypica hours (=100), by gender and workpace size 25% 2 Figure 8 shows that work ife baance (the fit between working hours and famiy or socia commitments) is better for those working in the education sector than in the as a whoe. However, the differences in the proportion of workers reporting a poor work ife baance are sma for women in sma and mediumsize workpaces and for men in micro workpaces and arge workpaces. Figure 8: Poor work ife baance, by gender and workpace size % % Tota Work organisation 4 When ooking at the reguarity of working time (working the same number of hours every day and the same number of days every week), arge differences exist across genders and workpace sizes in the education sector compared to the (Figure 7). In the sector as a whoe, women are more ikey than the average to have reguar working hours, whie the opposite is true for men. This pattern does not appy, however, for arge workpaces where both men and women have on average ess reguar working hours than the average. More men in microworkpaces report irreguar working hours than a other groups of workers in the sector. Teamwork Teamwork has been proposed as an aternative to work organisation modes based on high eves of abour division. As teamwork refects a variety of practices, it can aso assume a variety of forms. Different types of teamwork can be identified using the EWCS by ooking at the eve of autonomy within the teams. Overa, teamwork is equay prevaent in the education sector as in the as a whoe, with 64% of the education workforce working in a team of some kind, compared to 63% in the (Figure 9). There are, however, differences between occupations in the sector, as workers in manua occupations are consideraby ess ikey than workers in cerica

5 Manua Cerica occupations to work as part of a team. Teamwork with some autonomy is the most common form of teamwork among manua workers in education, and more common than for manua workers in the as a whoe; a higher-than-average share of cerica workers in the sector, on the other hand, report that they work in a team with much autonomy. Figure 9: Teamwork and team autonomy, by occupationa category No teamwork Team with no autonomy Team with some autonomy Team with much autonomy No teamwork Team with no autonomy Team with some autonomy Team with much autonomy 5% 1 15% 2 25% 3 35% 4 45% 5 Task rotation Task rotation is aso an important feature of work organisation. Depending on how it is impemented, task rotation may require different skis from the worker ( mutiskiing ) or may not ( fixed task rotation ) and is either controed by management or by the workers themseves ( autonomous ). Task rotation has been shown to be beneficia for workers we-being, and autonomous mutiskiing systems, in particuar, are associated with greater worker motivation as we as better company performance. The percentage of workers in education working in a task rotation system (42%) is ower than in the as a whoe (47%). The difference is particuary marked in sma and medium-sized workpaces and arge workpaces in the sector, in which the proportion of workers who report not working in any task rotation system (respectivey 57% and 62%) is consideraby higher than in the corresponding workpace sizes (5 and 53%) (Figure 10). In contrast to the, the prevaence of task rotation in education actuay decreases as workpace size increases. Management-controed mutiskiing is the most common form of teamwork across a workpace sizes, but both micro-workpaces and sma and medium-sized workpaces in education are characterised by an above-average incidence of autonomous mutiskiing in comparison to simiar workpaces in the. Large workpaces in education aso stand out for the higher-than-average incidence of autonomous fixed task rotation, reported by 6% of the workforce in comparison to ony 3% in simiar workpaces in the. Femae bosses As education is a femae-dominated sector, it is perhaps unsurprising that the proportion of workers who report having a femae boss (51%) is consideraby higher than the average (28%). Both the proportion of women (6) and men (32%) working in education who report having a femae boss is higher than the corresponding averages of 47% and 12% respectivey. However, the proportion of workers with a femae boss (51%) is sti we beow the proportion of femae workers (72%) in the sector. Skis and training Overa, the majority of workers in education say that their present skis correspond we with their duties (Figure 11). Across a age groups, however, workers Figure 10: Prevaence of task rotation, by workpace size No task rotation Autonomous fixed task rotation Autonomous mutiskiing Management-controed fixed task rotation Management-controed mutiskiing 5

6 Figure 11: Match between skis and tasks, by age <35 years years 50+ years Tota I need further training to cope we with my duties I have the skis to cope with more demanding duties My present skis correspond we with my duties 7 in education are consideraby more ikey to say they are under-skied than workers in the as a whoe and ess ikey to be over-skied athough a higher proportion of workers say they are over-skied than under-skied across a age groups. Young workers in education are most ikey to be underskied, whie oder workers (above the age of 50) are most ikey to be over-skied for their current duties. The percentage of workers in education who report they have received training provided or paid for by their empoyer is consideraby higher than in the for both women and men across a age groups (Figure 12). In each age group, however, men more often receive empoyer-paid training than their femae counterparts. Figure 12: Empoyer-paid training, by gender and age shows the combined resuts of these questions (an empoyee representative has been considered to be avaiabe if they are present in the workpace or when an issue was raised). Figure 13: Avaiabiity of an empoyee representative at the workpace, by workpace size Tota <35 years years 50+ years Tota <35 years years 50+ years Tota In 2010, 64% of in education reported that an empoyee representative was avaiabe compared to 52% of workers in the. As is the case in the, the more workers empoyed in the workpace, the higher the probabiity of having an empoyee representative athough the percentage of workers in arge workpaces in education who said that an empoyee representative was avaiabe is ower than the average for arge workpaces. 6 Empoyee representation The EWCS contains imited information on forma empoyee representation. It asks whether an empoyee representative is present in the workpace and whether workers have raised an issue with an empoyee representative in the past year. Figure 13 Psychosocia and physica environment Job autonomy and work intensity The psychosocia and physica environment has a substantia impact on workers we-being. According to the job demand and contro mode of the American socioogist Karasek (1979), workers are more ikey to suffer from work-reated stress when they are faced

7 Figure 14: Distribution of groups of workers by average eves of job autonomy and work intensity 80 Low strain EU median Work intensity Active SE: years LE: <35 years LE: years LE: years LE: 50+ years Job autonomy SE: 50+ years SE: <35 years SE: 50+ years SE: years EU median Job autonomy 55 SE: <35 years LE: 50+ years Passive Job strain Work intensity Note: LE = arge enterprise; SE = micro, sma or medium-sized enterprise with a high eve of demand whie being imited in the contro they have over the way in which they carry out their job. Figure 14 shows the ikeihood of workers in education suffering from work-reated stress. Groups of workers are potted aong two axes: job autonomy and work intensity. Overa, the education sector is characterised by beow-average eves of work intensity, as the vast majority of workers tend to fa in the quadrants on the eft hand side of the graph, beow the median for work intensity. The bottom eft quadrant in Figure 14 contains the averages for men under the age of 35 working in micro, sma and medium-sized workpaces, as we as for women aged 50 and over in arge workpaces. These groups of workers are ikey to be in passive jobs, characterised by ow eves of intensity and ow eves of autonomy. The risk of stress is ow in these jobs, but there are risks of frustration and ow motivation as the jobs ack chaenge, and workers have itte contro over what they do and how they do it. Most group averages fa within the ow strain quadrant: men under 35 in arge workpaces; men aged 35 and over in micro, sma and medium-sized workpaces; women 50 years and over in micro, sma and medium-sized workpaces; and women aged in arge workpaces. under 35 in smaer workpaces are on the boundary of this ow strain quadrant and the passive quadrant. over 50 in arge workpace are on the boundary of this ow strain and the active quadrant. Low strain jobs are characterised by reativey ow eves of work intensity and high eves of job autonomy. They pose a ow risk of stress, but workers are ess ikey to suffer from frustration and oss of motivation than those in passive jobs. They might, however, not be chaenged to reaise their fu potentia. The top right quadrant contains the average for men aged years in arge workpaces. These workers tend to be in active jobs, with high eves of work intensity and high eves of job autonomy. The average for men above 50 in arge estabishments fas on the boundary between ow-strain and active jobs. Athough their jobs can be very demanding, workers in the active quadrant have enough contro over the way they do their job and can deveop coping strategies through active earning. The most probematic category is job strain in the bottom right quadrant, which is empty in the education sector. The jobs of workers in this category are characterised by high eves of intensity and ow eves of autonomy, posing the risk of unheathy stress eves and unresoved strain, and consequenty a range of stress-reated inesses such as cardiovascuar disease and menta heath probems. Socia environment A good socia environment is characterised by the existence of socia support and the absence of abuse at work. Socia support can hep workers dea with high eves of work intensity. Gender differences emerge among workers in education for this indicator (Figure 15). In micro-workpaces, women have an aboveaverage score for good socia environment, whie men score beow the EU average in both micro-workpaces and sma and medium-sized workpaces. No substantia differences between the sector and the are found for men and women in arge workpaces. 7

8 Figure 15: Index of good socia environment ( = 100), by gender and workpace size 12% 1 8% 6% Figure 17: Not very we or not at a we informed about heath and safety risks at work, by workpace size 96 4% 2% Tota Tota Physica risks Exposure to ambient risk is the most prevaent physica risk in education as a whoe (Figure 16). Overa, however, eves of exposure to physica risks in the sector are consideraby ower than in the. There are, however, differences between workers in manua and cerica occupations. working in manua occupations in education report consideraby higher eves of exposure to posture- and movementreated and bioogica and chemica risks than average. On the other hand, both women and men in cerica occupations have ower-than-average eves of exposure to a risk types. In the sector as a whoe, 9% of workers report they were not very we or not at a we informed about workpace risks, compared to 1 in the (Figure 17). When ooking at workpace size, the proportion of workers in education reporting that they are not very we or not at a we informed is shown to increase with workpace size, which is the opposite pattern to workers in the as a whoe. Job quaity In the report Trends in job quaity in Europe, the authors constructed four indices of job quaity: earnings, prospects, intrinsic job quaity and working time quaity. The indices are buit using job characteristics that are unambiguousy associated with workers we-being. Figure 18 summarises job quaity in the education sector. It shows the average score for the sector on each of the indicators, with and without controing for the structura characteristics of the sector s workers (age, gender, workpace size, education eve and country), and for the. Job quaity in the education sector is sighty higher than in the as a whoe, as workers in the sector tend to have higher-than-average earnings, better working time quaity, greater intrinsic job quaity and better prospects. However, when controing for Figure 16: Indices of exposure to physica risks ( = 100), by gender and occupationa category Manua Cerica Manua Cerica A Posture- and movement-reated risks Bioogica and chemica risks Ambient risks

9 Figure 18: Job quaity in the human heath sector compared with Earnings Prospects 50 Working time quaity Intrinsic job quaity (controed) Note: Scores on a four indicators range from 0 to 100 structura characteristics of the workforce, a of these differences are reduced, with the earnings score for the education sector actuay faing beow the average suggesting that in terms of earnings workers in education are actuay worse off than workers with simiar profies and characteristics in other sectors. The difference between the sector and the with regard to intrinsic job quaity remains significanty positive, whie the differences observed in working time quaity and prospects are no onger statisticay significant when controing for structura characteristics. The higher-than-average eve of educationa attainment of the workforce in education is the strongest predictor for the higher observed scores in these two indicators. Heath and sustainabiity of work Working conditions can have both a positive and a negative impact on the heath of workers and on the sustainabiity of their jobs. Figure 19 shows that the education sector compares quite favouraby with the in heath and job sustainabiity outcomes. The proportion of workers who have been absent due to a work accident, who have poor sef-reported heath, who decare that their heath is at risk because of work and that work affects their heath negativey is ower in the education sector than in the. The share of workers who think they wi be abe to do their job at 60 is aso higher in the sector than in the. Leves of presenteeism (having worked when sick) reported by education workers, however, are higher in comparison to the average. When controing for the structura characteristics of the workforce in the sector (gender, age, education, workpace size and country), the differences between the sector and the in the ower ikeihood of education workers to decare that work affects their heath negativey and that their heath is at risk because of work remain statisticay significant. The same is true for the greater ikeihood of workers in education to report that they have worked when sick suggesting that presenteeism is an issue that needs to be addressed in the sector. On the other hand, the positive differences between the sector and the in reation to poor sef-reported heath, absence due to work accident and abiity to do one s job at 60 are not statisticay significant when controing for structura characteristics. They seem instead to be expained by the country distribution of the workforce in the education sector and by the higher-thanaverage eve of education of the sector s workforce. 9

10 Figure 19: Heath and sustainabiity of work Absent due to work accident Poor sef-reported heath Heath at risk because of work Work affects heath negativey Presenteeism Abe to do job at 60 Figure 20 again shows that workers in the education sector do not differ much from the average in the reported number of heath symptoms, menta webeing score, and eve of absenteeism. However, when incuding gender, age, education, workpace size and the country distribution of the workforce in the mode, education workers are found to have a sighty better menta we-being than workers in the. This suggests that given the profie of workers in education particuary given the arge proportion of women and the reativey high eve of education workers in education have a reativey good menta we-being. It is important to keep in mind that the impact of work on heath is a very gradua process that can take a ong time and cannot be fuy captured in a crosssectiona survey. The resuts in this section are ikey to underestimate the often negative heath effects that physicay and psychoogicay strenuous working conditions can have. Figure 20: Indices of heath symptoms, menta we-being and absenteeism ( = 100) ta we-being Absenteeism Number of heath symptoms

11 References Eurofound (2012), Trends in job quaity in Europe, Pubications Office of the European Union, Luxembourg. Eurostat (2013), EU Labour Force survey database, avaiabe at statistics/search_database Karasek, R. A. Jr (1979), Job demands, job decision atitude, and menta strain: Impications for job redesign, Administrative Science Quartery, Vo. 24, pp

12 European Working Conditions Survey Eurofound deveoped its European Working Conditions Survey (EWCS) in 1990 in order to provide high-quaity information on iving and working conditions in Europe. Five waves of the survey have been carried out to date, enabing ong-term trends to be observed and anaysed. The EWCS interviews both and sef-empoyed peope on key issues reated to their work and empoyment. Fiedwork for the fifth EWCS took pace from January to June 2010, with amost 44,000 workers interviewed in their homes in 34 countries, Norway, the former Yugosav Repubic of Macedonia, Turkey, Abania, Montenegro and Kosovo. The 5th EWCS was impemented by Gaup Europe, who worked within a strong quaity assurance framework to ensure the highest possibe standards in a data coection and editing processes. The questionnaire covered issues such as precarious empoyment, eadership styes and worker participation as we as the genera job context, working time, work organisation, pay, work-reated heath risks, cognitive and psychosocia factors, work-ife baance and access to training. A number of questions were incuded to capture the impact of the economic downturn on working conditions. For more information on the EWCS, see Sectora anaysis The report Working conditions and job quaity: Comparing sectors in Europe and the series of 33 sectora information sheets aim to capture the diversity prevaent across sectors in Europe in terms of working conditions and job quaity. The report pinpoints trends across sectors in areas such as working time and work ife baance, work organisation, skis and training, empoyee representation and the psychosocia and physica environment. It identifies sectors that score particuary we or particuary poory in terms of job quaity and sheds ight on differences between sectors in terms of heath and we-being. For more information, see Further information Gijs van Houten, Research Officer European Foundation for the Improvement of Living and Working Conditions Wyattvie Road, Loughinstown, Dubin 18, Ireand Teephone: (+35 1) Emai: Website: EF/13/84/EN 17

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