and second level university master Academic Year 2013/14 QoLexity Measuring, Monitoring and Analysis of Quality of Life and its Complexity

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1 and second level university master Academic Year 2013/14 QoLexity Measuring, Monitoring and Analysis of Quality of Life and its Complexity in cooperation with Eurostat DIDACTIC ORGANIZATION

2 A. Concepts and tools In Florence (except when indicated) Total: 7 credits 42 hours A.1 Towards a common language: general concepts and their meanings Alberto Peruzzi Filosofia Teoretica M-FIL/01 A.1.1 Complexity Alberto Peruzzi 2 FI A.1.2 Quality and quantity Alberto Peruzzi 2 FI A.1.3 Multidimensionality Alberto Peruzzi 2 FI A.1.4 Explanation and forecasting (I) Alberto Peruzzi 2 FI A.1.5 Explanation and forecasting (II) Alberto Peruzzi 2 FI A.1.6 Stability and change Alberto Peruzzi 2 FI A.1.7 Progress and growth Alberto Peruzzi 2 FI A.1.8 Subjective and inter-subjective experience: different levels and dimensions (I) Rocco Sacconaghi 2 FI A.1.9 Subjective and inter-subjective experience: different levels and dimensions (II) Rocco Sacconaghi 2 FI

3 A.2 Quality of life and related concepts Giampaolo Nuvolati Sociologia dell Ambiente e del territorio SPS/10 Quality of life and its definition A.2.1 Quality of Life: review of the main concepts and domains Giampaolo Nuvolati 2 FI A.2.2 Measures of wellbeing: historical review Tommaso Rondinella 2 FI A.2.3 Quality of life and sustainability: introduction to basic concepts Fabiola Riccardini 2 FI A.2.4 Quality of life and sustainability: methods and measures Fabiola Riccardini 2 FI A.2.5 Quality of life and sustainability: empirical evidences Fabiola Riccardini 2 FI A.2.6 Quality of life and its relationship with equity, polarization, inequality Marco Fattore 2 FI A.2.7 Quality of life and urban development Giampaolo Nuvolati 2 FI A.2.8 Statistical knowledge and policy decision Enrico Giovannini 4 FI Additional lessons A.2.9 Quality of life and the capabilities approach Mario Biggeri 2 FI A.2.10 Wellbeing and identity Anna Loretoni 2 FI Aula Magna - Polo Didattico "La Crocetta" - Università di Firenze (via Laura 48)

4 A.3 Get prepared: acquiring technical tools Daniele Vignoli Demografia SECS-S/04 1 credit (6 hours) A.3.1 Using Statistical packages: introduction to STATA Daniele Vignoli (UNIFI) 2 FI A.3.2 Using R: introduction Emanuela Dreassi (UNIFI) 2 FI A.3.3 Using R: spatial statistics Emanuela Dreassi(UNIFI) 2 FI

5 B. Data In Rome (except as indicated) Total: 12 credits 72 hours B.1 Quality-of-life data 1 Linda Laura Sabbadini Statistica Sociale SECS-S/05 General issues 6 credits (36 hours) B.1.1 Social changes and official statistics changes Linda Laura Sabbadini 4 FI B.1.2 Social monitoring and reporting Heinz-Herbert Noll 4 FI B.1.3 GDP & beyond: the European strategy (I) Marleen De Smedt 2 RM B.1.4 GDP & beyond: the European strategy (II) Donatella Fazio 2 RM B.1.5 Social statistics for social policies Chiara Saraceno 4 RM Focus on particular measuring domains B.1.7 Demographic trends Valerio Terra Abrami 2 RM B.1.8 Education and culture Maria Pia Sorvillo 2 RM B.1.9 Family and social networks Social participation Romina Fraboni 2 RM B.1.10 Life styles Lidia Gargiulo 2 RM B.1.11 A gender approach to data analysis Sara Demofonti 2 RM B.1.12 Crime Maria Giuseppina Muratore 2 RM B.1.13 Measuring time use Tania Cappadozzi 2 RM B.1.14 Work Federica Pintaldi 2 RM B.1.15 Environment and landscape Angela Ferruzza 2 RM 1 This module aims at exploring (i) the role of official statistics in following social changes, and (ii) the possibility to build a narrative concerning social change through data. In particular, it will be described how observation of social phenomena through official statistics develops according to the evolution of social themes.

6 B.1.16 Environment and landscape Alessandra Ferrara 2 RM B.2 Data collection 2 Linda Laura Sabbadini Statistica Sociale SECS-S/05 General issues 6 credits (36 hours) B.2.1 Designing subjective questions: international experiences Adolfo Morrone 2 RM B.2.2 Data quality and observation errors Marina Signore 2 RM B.2.3 The art of designing a questionnaire. I Sante Orsini 2 RM B.2.4 The art of designing a questionnaire. II Silvia Montecolle 2 RM B.2.5 Designing a survey: the sample design Claudio Ceccarelli 4 RM B.2.6 Designing a survey: the choice of data collection technique Clelia Romano 4 RM B.2.7 The new frontiers of data collection: integration of administrative data, sample surveys, census I Saverio Gazzelloni 2 RM B.2.8 The new frontiers of data collection: integration of administrative data, sample surveys, census II Giuseppe Garofalo 2 RM Collecting data on particular social groups and topics B.2.9 Integration of sources in measuring migrants quality-of-life I Cinzia Conti 2 RM B.2.10 Integration of sources in measuring migrants quality-of-life II Monica Perez 2 RM B.2.11 How to measure discrimination and stereotypes Clelia Romano 2 RM B.2.12 How to measure new emerging forms of households Cristina Freguja 2 RM B.2.13 Health-related quality of life Viviana Egidi 2 RM B.1.14 How to measure health and mortality Roberta Crialesi 2 RM 2 This module aims at exploring the methodologies (survey design, questionnaire construction, data collection techniques) aimed at measuring social phenomena with particular reference to official statistics.

7 B.1.15 How to measure income and poverty Nicoletta Pannuzi 2 RM B.1.16 How to measure homelessness Cristina Freguja 2 RM

8 C. Analytical approaches C.1 Indicators: from reality to reading the reality Filomena Maggino Statistica Sociale SECS-S/05 How to make indicators a knowledge instrument Total 15 credits 90 hours C.1.1 The conceptual and logical process in defining indicators Filomena Maggino 2 FI C.1.2 Choosing the future through indicators Enrico Giovannini 4 FI C.1.3 Systems of social indicators Heinz-Herbert Noll 4 FI C.1.4 How to relate them: composite or dashboard, synthesis and aggregation Marco Fattore 2 FI Applications C.1.5 Fuzzy approach Achille Lemmi 4 FI C.1.6 Relational mapping Marco Fattore 2 FI

9 C.2 Indicators: analytical tools and strategies Filomena Maggino Statistica Sociale SECS-S/05 Aggregative approach: composite indicators C.2.1 Constructing complex indicators: technical issues. I Filomena Maggino 2 FI C.2.2 Constructing complex indicators: technical issues: composite indicators Matteo Mazziotta 4 FI C.2.3 Constructing complex indicators: technical issues: counting approach Marco Fattore 2 FI Non aggregative approach: the case of ordinal data C.2.4 Constructing complex indicators: the partial order approach Marco Fattore 4 FI C.2.5 Subjective indicators: specific issues Filomena Maggino 2 FI Assessing complex indicators C.2.6 Sensitivity analysis Matteo Mazziotta 2 FI

10 C.3 Quality-of-life data analysis: pathways to modelling Alessandra Petrucci Statistica SECS-S/01 C.3.1 Reducing complexity of data: dimensional analysis Filomena Maggino 2 FI C.3.2 Geographical orientation of Quality of Life data Alessandra Petrucci 2 FI C.3.3 Narratives and data structure: the role of statistical information systems Cristina Martelli 2 FI C.3.4 Investigating data structure: social mining (I) Dino Pedreschi 2 FI C.3.5 Investigating data structure: social mining (II) Fosca Giannotti 2 FI C.3.6 From large survey data to subpopulations: small area estimation methods (I) Monica Pratesi 2 FI C.3.7 From large survey data to subpopulations: small area estimation methods (II) Caterina Giusti 2 FI C.3.8 From large survey data to subpopulations: small area estimation methods (III) Monica Pratesi 4 FI

11 C.4 Quality-of-life data analysis: looking for explanations Carla Rampichini Statistica SECS-S/01 C.4.1 Relating micro and macro quality of life aspects: the multilevel approach I Carla Rampichini 4 FI C.4.2 Relating micro and macro quality of life aspects: the multilevel approach II Leonardo Grilli 2 FI C.4.3 Approaches in analyzing change Filomena Maggino 2 FI C.4.4 Evaluating individual changes: analysis of panel quality of life data Arnstein Aassve 4 FI C.4.5 Measuring latent, manifest and longitudinal poverty and quality of life Gianni Betti 4 FI C.4.6 Life course analysis Daniele Vignoli 2 FI

12 C.5 Making all concrete 3 Daniele Vignoli Demografia SECS-S/04 C.5.1 Relationship between quality-of-life and demographic events Letizia Mencarini 2 FI C.5.2 Explaining life satisfaction across Europe Daniele Vignoli 2 FI C.5.3 Territorial representation of quality-of-life data Marco Mauri 4 FI C.5.4 Measuring wellbeing at local level: from individuals to communities Michela Guerini 2 RM C.5.5 Urban development and quality of life Michela Guerini 2 RM C.5.6 Measuring vulnerability Adolfo Morrone 2 RM C.5.7 Latent class approaches: the case of social exclusion Elena Pirani 2 FI C.5.8 Technology and quality of life Katarzyna Wac 2 FI 3 Selected case studies as well as different and specific themes will be presented through a multidisciplinary approach and completed with lab-sections.

13 D. Representing and communicating This module has been adopted as one of the activities managed by OECD in the ambit of the Web-COSI project (http://www.webcosi.eu/) In Florence (except as indicated) D.1: Representing quality-of-life data and results Carlo Sorrentino Sociologia dei Processi Culturali e Comunicativi SPS/08 8 credits 48 hours D.1.1 Representing the complexity: data visualization issues Paolo Ciuccarelli 4 RM D.1.2 Graphics as an instrument for telling stories. Dashboards Stefano de Francisci 4 RM D.1.3 Communication aspects of statistical graphics: how to use graphs to underline the message Marco Trapani 2 FI D.1.4 How to prepare a successful presentation Marco Trapani 4 FI D.1.5 How to lie with quality-of-life statistics Marco Trapani 2 FI D.1.6 Shiny Stefano Barberis 2 FI

14 D.2 Communicating quality-of-life results Carlo Sorrentino Sociologia dei Processi Culturali e Comunicativi SPS/08 D.2.1 Public communication: the case of quality of life results Carlo Sorrentino 2 FI D.2.2 Strategies in communicating information on QoL Data, media and public opinion: problems and strategies Donato Speroni 6 FI D.2.3 Statistics and political communication: theories and methods Silvano Cacciari 4 FI D.2.4 How knowledge can be transferred into policy Katherine Scrivens 2 FI D.2.5 Communication and policy use of indicators Donatella Fazio & Marina Signore 2 RM D.2.6 Politics, policy and quality of democracy Leonardo Morlino 2 FI

15 D.3 Putting all together Daniele Vignoli Demografia SECS-S/04 2 credits (6x2 = 12 hours) D.3.1 Start up QoLexity team 2 FI D.3.2 Wiki training Marco Trapani 2 FI D.3.3 Selecting a dataset and defining an analytical project on the selected dataset Daniele Vignoli 4 FI D.3.4 Preparing a presentation of the results and delivering it in a public presentation (tutoring) Marco Trapani 4 FI Meeting QoLexity team 4 FI Presentation of the theses QoLexity Committee FI

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