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Time in Social Sciences: Approaches and Measures

Учебный год
Обучение ведется на английском языке
Курс по выбору
Когда читается:
1-й курс, 2, 3 модуль


Course Syllabus


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 (themes 1-4), creating one’s own ideas and hypotheses (theme 5), choosing appropriate methods of analysis (themes 6-8), running analyses (theme 9), and making conclusions (theme 10). 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 know the theories of generations and their practical applications not only in scientific research but also in business and public administration
  • to be able to apply the generational approach to their practical needs
  • to know the three dimensions of time: age, period and cohort (and two more dimensions: stage of life and place) and master distinguishing them
  • to be able to distinguish the effects of age, period and generation
  • to know the life-course approach and its important multidisciplinary role
  • to be able to use the core terms and methods of the life-course approach
  • to know the different concepts of the transition to adulthood and the approaches to extracting its markers
  • to be able to distinguish different approaches to the transition to adulthood and offer their own approaches
  • to know the scope of the methods of the analysis of biographies and distinguish the differences between qualitative and quantitative approaches
  • to be able to account for the basic types of data for a valid study of time
  • to be able to critically discuss the limitations of the chosen methods of studying time processes
  • 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 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 have the skill of analysing biographical events in MS Excel and IBM SPSS
  • to be able to apply acquired knowledge about time to their own projects
  • 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
Course Contents

Course Contents

  • Introduction. Approaches to Time in the Social Sciences
    The first session lays out the course plan and requirements for student participation and introduces the main concepts of time in the social sciences, such as: chronological and temporal time; dimensions of time; and visualisation of temporal processes.
  • Dimensions of Time: APC-Analysis
    The session introduces the Lexis grid and Age-Period-Cohort analysis (APC). We discuss the importance of place and the stage of life in addition to APC. We practice using APC approach.
  • Theories of Generations
    The session discusses and compares different approaches to the concept of generation and cohorts. We analyse the works of K. Mannheim, N. Ryder and others.
  • Life Course Approach
    We study and compare the differences between the concepts of life span, life cycle and life course approaches (LCA). We learn the basic terms of the LCA.
  • Life Course Stages. Transition to Adulthood
    We critically analyse different classifications of life stages. We discover the importance of studying the transition to adulthood and the approaches to the analysis of this life stage and existing exploratory concepts.
  • Approaches to Measuring Time in the Social Sciences
    We study qualitative and quantitative approaches to the analysis of biographies. We discuss the advantages and disadvantages of these methods and the opportunity of mixing them.
  • Measures of Biographical Events Occurrence
    We study quantitative methods of analysis of biographical events by dividing them into four major groups: quantum, timing, tempo and sequencing.
  • Introduction to Sequence Analysis and Event History Analysis
    We study the advanced methods of analysis of quantitative biographical data and learn how to apply them to students’ research questions.
  • Practice in MS Excel, IBM SPSS and R
    We practice the usage of quantitative methods of analysis in MS Excel, IMB SPSS and R. Students learn how to prepare data; how to create dates, ages and intervals; how to calculate mean, median and modal ages; how to use statistical tests and crosstabs; and how to apply Event History Analysis.
  • Conclusion of the Course and Feedback on Research Projects
    This session brings together all the approaches to time in the social sciences and is devoted to the discussion of the students’ research projects.
Assessment Elements

Assessment Elements

  • non-blocking Quizzes
    This element of control was conducted before covid-19 quarantine
  • non-blocking Homework assignment 1: Transition to adulthood
    Write a small essay (1-2 pages) about the life course composition and the transition to adulthood in your country. This element of control was conducted before covid-19 quarantine
  • non-blocking Homework assignment 2: Collecting biographies
    Collect biographical events of the members of a family of your choice and write a technical report. This element of control was conducted before covid-19 quarantine
  • non-blocking Homework assignment 3: Lexis grid and other methods of analysis
    Draw the events you collected on the Lexis grid and write a small essay where you compare the life courses of the members of the family you chose. Choose the approach for further analysis of the biographies you have. This element of control was conducted before covid-19 quarantine
  • non-blocking Final project
    For the final project, students will need to merge all three home tasks into one document, organise its structure according to the requirements, add the new information and write an introduction and conclusion. After covid-19 quarantine, this element of control was not changed: students sent their final projects to the teacher's e-mail as it was planned.
  • non-blocking Debates
    Students are being divided into two teams. Each team has its own position: for or against the suggested statement. Each team has 10 minutes to develop the arguments in support of their position. After 10 minutes, each member of each team, one by one, shares his/her argument and defend it in front of counter arguments of the opposite team.
Interim Assessment

Interim Assessment

  • Interim assessment (3 module)
    Quizzes – 25%. Debates – 5%. Home assignment 1 – 10%. Home assignment 2 – 10%. Home assignment 3 – 10%. Final project – 40%. No exam.


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
  • 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. 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
  • 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

  • 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, 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
  • 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