Unitary Social Science for Causal Understanding: Experiences and Prospects of Life Course Research

Authors

  • Martin Diewald Gerhard-Mercator-Universität Duisburg, Fachbereich 1/Soziologie, Duisburg Germany

DOI:

https://doi.org/10.25336/P6MS41

Abstract

Longitudinal data are superior to cross-sectional data for explaining social processes. Yet, the existing division of labour in social science is a serious handicap for causal understanding of human behaviour. This is demonstrated in this article with the quite unrelated coexistence of sociological research on life histories and psychological research on individual development. Two examples are discussed: the intergenerational reproduction of social inequalities and the openness versus closedness of labour markets. Though there is an increasing awareness of problems of selectivity and unobserved heterogeneity in conventional social research, statistical modelling of these problems cannot replace the need for transdiciplinary data collection and research.

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Published

2001-12-31

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Section

Articles