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Regular version of the site
Master 2022/2023

Time in Social Sciences: Approaches and Measures

Type: Elective course (Comparative Social Research)
Area of studies: Sociology
Delivered by: Department of Demography
When: 1 year, 2, 3 module
Mode of studies: offline
Open to: students of all HSE University campuses
Master’s programme: Comparative Soсial Research
Language: English
ECTS credits: 6
Contact hours: 48

Course Syllabus

Abstract

The course consists of two parts: theoretical (before the new year) and practical (after the new year). First, we will learn the main approaches of understanding time in the social sciences and then develop the skills of qualitative and quantitative analysis of biographies. The course will provide students experience in real academic research. The themes and tasks are structured in the same manner that scientists conduct research: studying theoretical concepts, creating one’s own ideas and hypotheses, choosing appropriate methods of analysis, running analyses, and making conclusions. Students may choose either a qualitative or a quantitative approach for their final projects, but the core of the tasks aims to develop skills in both types of analysis. The tasks not only have academic value but also develop the knowledge about students’ own family scenarios and let them learn what role life course change and generational shifts play in their own lives. After this course, the students will have a structured view of different concepts and aspects of time (APC-method, theory of generations, life-course approach and transition to adulthood). They will be able to work with biographical events in MS Excel and IBM SPSS, i.e., to analyse dates and ages of events, the intervals between them, the numbers of events, their order and their risk of occurrence.
Learning Objectives

Learning Objectives

  • To give the students the most important knowledge about time and methods for working with time in the social sciences
  • To enrich the scope of concepts and theories which students may use for their academic and practical needs
  • To provide students experience in real research work: to let them create research ideas and hypotheses, develop their own methodological approaches and achieve visible results
  • To master the qualitative and quantitative methods of analysis of biographical events and other processes developing in time
Expected Learning Outcomes

Expected Learning Outcomes

  • to be able to account for the basic types of data for a valid study of time
  • to be able to apply acquired knowledge about time to their own projects
  • to be able to apply the generational approach to their practical needs
  • to be able to calculate mean, median and modal ages; the cumulative shares of events by certain ages; the intervals between events; and the risks of events occurring, inter alia
  • to be able to choose and apply the most appropriate methods of biographical events analysis
  • to be able to correctly interpret the results of Sequence Analysis and Event History Analysis
  • to be able to critically discuss the limitations of the chosen methods of studying time processes
  • to be able to distinguish different approaches to the transition to adulthood and offer their own approaches
  • to be able to distinguish the effects of age, period and generation
  • to be able to use the core terms and methods of the life-course approach
  • to have the skill of analysing biographical events in MS Excel and IBM SPSS
  • to have the skill of conducting their own qualitative or quantitative research
  • to know the difference between natural and social time and between chronological and temporal time
  • to know the different approaches to the classification of life stages
  • to know the different concepts of the transition to adulthood and the approaches to extracting its markers
  • to know the life-course approach and its important multidisciplinary role
  • to know the scope of the methods of the analysis of biographies and distinguish the differences between qualitative and quantitative approaches
  • to know the theories of generations and their practical applications not only in scientific research but also in business and public administration
  • to know the three dimensions of time: age, period and cohort (and two more dimensions: stage of life and place) and master distinguishing them
Course Contents

Course Contents

  • Introduction. Approaches to Time in the Social Sciences
  • Dimensions of Time: APC-Analysis
  • Theories of Generations
  • Life Course Approach
  • Life Course Stages. Transition to Adulthood
  • Approaches to Measuring Time in the Social Sciences
  • Measures of Biographical Events Occurrence
  • Tempo: Event History Analysis
  • Structure, Quantum and Timing of Events Occurrence
  • Sequencing: Sequence Analysis. Conclusion of the Course
Assessment Elements

Assessment Elements

  • non-blocking Quizzes and class activities
    We will have two quizzes, one debate in the class and one group work
  • non-blocking Home assignments
    Three home assignments combined with one idea - gradually to prepare a final paper
  • non-blocking Final project
    Students need to choose one of two options: qualitative (qual) or quantitative (quant) project: qual requires conducting three semi-structured interviews; quant requires analysing a testing dataset.
Interim Assessment

Interim Assessment

  • 2022/2023 3rd module
    0.3 * Home assignments + 0.3 * Quizzes and class activities + 0.4 * Final project
Bibliography

Bibliography

Recommended Core Bibliography

  • A training manual for event history analysis using longitudinal data. (2019). https://doi.org/10.1186/s13104-019-4544-1
  • Benson, J. E., & Elder, G. H. (2011). Young Adult Identities and Their Pathways: A Developmental and Life Course Model. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsbas&AN=edsbas.F5C66FBF
  • Billari, F. C. (2001). Sequence Analysis in Demographic Research. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsbas&AN=edsbas.66F333F7
  • Ciesielska, M., & Jemielniak, D. (2018). Qualitative Methodologies in Organization Studies : Volume I: Theories and New Approaches. Cham, Switzerland: Palgrave Macmillan. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=1642593
  • Ciesielska, M., & Jemielniak, D. (2018). Qualitative Methodologies in Organization Studies : Volume II: Methods and Possibilities. Cham, Switzerland: Palgrave Macmillan. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=1658712
  • Costa Ruibal, Ò. (2007). Biographical Research Methods. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsrac&AN=edsrac.191254
  • Dayal, V. (2015). An Introduction to R for Quantitative Economics : Graphing, Simulating and Computing. New Delhi: Springer. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=967484
  • Elder, G. H. (1998). The life course as developmental theory. Child Development, 69(1), 1. https://doi.org/10.2307/1132065
  • Families across the life course, White, J. M., 2013
  • Francesco C. Billari, Johannes Fürnkranz, & Alexia Prskawetz. (2000). Timing, Sequencing, and Quantum of Life Course Events: A Machine Learning Approach. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsbas&AN=edsbas.B096C278
  • Heidegger, M., & Farin, I. (2011). The Concept of Time : The First Draft of Being and Time. London: Continuum. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=1717351
  • Introduction to R. (2016). France, Europe: HAL CCSD. https://doi.org/10.1051/eas/1677002
  • Jakub Gałęziowski. (2019). Oral History and Biographical Method. Common Framework and Distinctions Resulting from Different Research Perspectives. Przeglad Socjologii Jakosciowej, (2), 76. https://doi.org/10.18778/1733-8069.15.2.05
  • Mills, M. (DE-588)143567098, (DE-576)27501360X. (2011). Introducing survival and event history analysis / Melinda Mills. Los Angeles [u.a.]: Sage. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edswao&AN=edswao.334939798
  • Morteza Aalabaf‐Sabaghi. (2019). A Practical Guide to Age–Period–Cohort Analysis: the Identification Problem and Beyond. Journal of the Royal Statistical Society Series A, (2), 715. https://doi.org/10.1111/rssa.12433
  • Norris, G., Cramer, D., Howitt, D., & Qureshi, F. (2013). Introduction to Statistics with SPSS for Social Science. Abingdon: Routledge. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=960264
  • Puur, A., Rahnu, L., Maslauskaite, A., Stankuniene, V., & Zakharov, S. (2012). Transformation of Partnership Formation in Eastern Europe: The Legacy of the Past Demographic Divide. Journal of Comparative Family Studies, 43(3), 389–417. https://doi.org/10.3138/jcfs.43.3.389
  • Ryder, N. B. (1965). The Cohort as a Concept in the Study of Social Change. American Sociological Review, 30(6), 843–861. https://doi.org/10.2307/2090964
  • The Social Stratification of Choice in the Transition to Adulthood. (2019). Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsbas&AN=edsbas.4796AAB6
  • The sociology of Karl Mannheim : with a bibliographical guide to the sociology of knowledge, ideological analysis, and social planning, Remmling, G. W., 2016
  • Van Deusen, N., & Koff, L. M. (2016). Time : Sense, Space, Structure. Leiden: Brill. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=1234517

Recommended Additional Bibliography

  • Age studies : a sociological examination of how we age and are aged through the life course, Pickard, S., 2016
  • Ages, generations and the social contract : the demographic challenges facing the welfare state, , 2007
  • Amelia, R., Dimitri, M., Leen, H., AMSIB (CEDIS), & Faculteit Business en Economie. (2018). Establishing Typologies for Diverging Career Paths through the Life Course: A Comparison of two Methods. The Electronic Journal of Business Research Methods, 16(3), 139–149. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edshbo&AN=edshbo.amsterdam.pure.oai.pure.hva.nl.publications.39749167.9818.4227.aef8.4119c51ffe50
  • Ann Berrington, Juliet Stone, & Éva Beaujouan. (2015). Educational differences in timing and quantum of childbearing in Britain. Demographic Research, (26), 733. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsrep&AN=edsrep.a.dem.demres.v33y2015i26
  • Ari Klængur Jónsson. (2017). Childbearing trends in Iceland, 1982-2013: Fertility timing, quantum, and gender preferences for children in a Nordic context. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsbas&AN=edsbas.72F43805
  • Back, K. W., & American Association for the Advancement of Science. (2018). Life Course : Integrative Theories And Exemplary Populations. New York, NY: Routledge. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=2204186
  • Becker, G. S., Murphy, K. M., Kominers, S. D., & Spenkuch, J. L. (2018). A Theory of Intergenerational Mobility. Journal of Political Economy, 126, S7–S25. https://doi.org/10.1086/698759
  • BELLEZZA, S., PAHARIA, N., & KEINAN, A. (2017). Conspicuous Consumption of Time: When Busyness and Lack of Leisure Time Become a Status Symbol. Journal of Consumer Research, 44(1), 118–138. https://doi.org/10.1093/jcr/ucw076
  • Causal Effects of the Timing of Life-course Events : Age at Retirement and Subsequent Health. (2017). Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsbas&AN=edsbas.B5D5BF0
  • Cohort profile:The DANish LIFE course (DANLIFE) cohort, a prospective register-based cohort of all children born in Denmark since 1980. (2019). Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsbas&AN=edsbas.B574F7B2
  • Ellegård, K. (2019). Thinking time geography : concepts, methods and applications. Sweden, Europe: Linköpings universitet, Tema teknik och social förändring. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsbas&AN=edsbas.C5068A5F
  • Feldman, L. P., & Hornik, J. (1981). The Use of Time: An Integrated Conceptual Model. Journal of Consumer Research, 7(4), 407–419. https://doi.org/10.1086/208831
  • Francesco C. Billari, & Chris Wilson. (2001). Cohort dynamics in the transition to adulthood in contemporary Western Europe. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsbas&AN=edsbas.BABA1EEA
  • Francesco C. Billari, & Chris Wilson. (2001). Convergence towards diversity? Cohort dynamics in the transition to adulthood in contemporary Western Europe. MPIDR Working Papers. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsrep&AN=edsrep.p.dem.wpaper.wp.2001.039
  • Francesco C. Billari, Johannes Fürnkranz, & Alexia Prskawetz. (2000). Timing, sequencing and quantum of life course events: a machine learning approach. MPIDR Working Papers. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsrep&AN=edsrep.p.dem.wpaper.wp.2000.010
  • Genders in the life course : demographic issues, , 2007
  • Influences of the family of origin on the timing and quantum of fertility in The Netherlands. (2009). Population Studies. A Journal of Demography, 63(1), 71–85. https://doi.org/10.1080/00324720802621575
  • Junyong In, & Dong Kyu Lee. (2019). Survival analysis: part II - applied clinical data analysis. Korean Journal of Anesthesiology, 72(5), 441–457. https://doi.org/10.4097/kja.19183
  • Kotlikoff, L. J. (1988). Intergenerational Transfers and Savings. Journal of Economic Perspectives, 2(2), 41–58. https://doi.org/10.1257/jep.2.2.41
  • Kunkel, S., Chahal, J., Whittington, F. J., & Brown, J. S. (2014). Global Aging : Comparative Perspectives on Aging and the Life Course. New York: Springer Publishing Company. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=692343
  • Lengen, C., Timm, C., & Kistemann, T. (2019). Place identity, autobiographical memory and life path trajectories: The development of a place-time-identity model. Social Science & Medicine, (C), 21. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsrep&AN=edsrep.a.eee.socmed.v227y2019icp21.37
  • Nicola Barban, & Francesco Billari. (2011). Classifying life course trajectories: A comparison of latent class and sequence analysis. Working Papers. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsrep&AN=edsrep.p.don.donwpa.041
  • Schullery, N. M. (2013). Workplace Engagement and Generational Differences in Values. Business Communication Quarterly, 76(2), 252–265. https://doi.org/10.1177/1080569913476543
  • Shorrocks, A. F. (1975). The Age-Wealth Relationship: A Cross-Section and Cohort Analysis. The Review of Economics and Statistics, (2), 155. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsrep&AN=edsrep.a.tpr.restat.v57y1975i2p155.63
  • Spielauer, M., & Städtner, K. (2018). The Influence of Education on quantum, timing and spacing of births in Austria. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsbas&AN=edsbas.A686741F
  • Tesárková, K. H., & Kurtinová, O. (2018). Lexis in Demography. Cham, Switzerland: Springer. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=1601775
  • Visualizing compositional data on the Lexis surface. (2017). Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsbas&AN=edsbas.75C95309
  • Vocational Education and Employment: Explaining Cohort Variations in Life Course Patterns. (2019). Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsbas&AN=edsbas.6C9C8492
  • W. Vaupel, J., Rau, R., M. Muszynska, M., & Bohk-Ewald, C. (2018). Visualizing Mortality Dynamics in the Lexis Diagram. Web server without geographic relation, Web server without geographic relation (org): Springer. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsbas&AN=edsbas.9988DFCB
  • Wheatley, D., & Buglass, S. L. (2019). Social network engagement and subjective well‐being: a life‐course perspective. British Journal of Sociology, 70(5), 1971–1995. https://doi.org/10.1111/1468-4446.12644

Presentation

  • Video
  • Programme of the course

Authors

  • CHEKLINA EKATERINA MIKHAYLOVNA
  • FRYOLIKH KRISTIAN -
  • MITROFANOVA EKATERINA SERGEEVNA