Embracing complexity in social science research

Rafael Quintana ()
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Rafael Quintana: University of Kansas

Quality & Quantity: International Journal of Methodology, 2023, vol. 57, issue 1, No 2, 15-38

Abstract: Abstract Social and behavioral phenomena are fundamentally complex in the sense that they are shaped by many interdependent causes. Researchers that adopt a complex systems perspective have argued that, rather than focusing on a single causal relationship at a time, we need to investigate how the interaction or combination of different factors generate specific outcomes. The main objective of this article is to review three methodological frameworks that have been used to investigate the interdependencies between causal factors, which is often referred to as the study of causal complexity. The three frameworks are: interaction analysis, which investigates effect heterogeneity; structural analysis, which investigates causal mechanisms; and configurational analysis, which investigates sufficient and necessary conditions. I summarize the goals and recent developments of these techniques, as well as two theoretical frameworks—intersectionality theory and the so-called “heterogeneity revolution”—that stress the importance of investigating causal complexity in social science research.

Keywords: Causal complexity; Intersectionality; Interaction analysis; Structural analysis; Configurational analysis (search for similar items in EconPapers)
Date: 2023
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DOI: 10.1007/s11135-022-01349-1

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