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Causality in Contemporary American Sociology: An Empirical Assessment and Critique
Author(s) -
Vaidyanathan Brandon,
Strand Michael,
ChoiFitzpatrick Austin,
Buschman Thomas,
Davis Meghan,
Varela Amanda
Publication year - 2016
Publication title -
journal for the theory of social behaviour
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.615
H-Index - 51
eISSN - 1468-5914
pISSN - 0021-8308
DOI - 10.1111/jtsb.12081
Subject(s) - causal inference , causality (physics) , epistemology , causal model , causal reasoning , set (abstract data type) , causal structure , inference , sociology , causal decision theory , empirical research , cognition , psychology , computer science , econometrics , artificial intelligence , philosophy , mathematics , physics , quantum mechanics , neuroscience , programming language , statistics , business decision mapping , decision support system , decision engineering
Using a unique data set of causal usage drawn from research articles published between 2006–2008 in the A merican J ournal of S ociology and A merican S ociological R eview, this article offers an empirical assessment of causality in American sociology. Testing various aspects of what we consider the conventional wisdom on causality in the discipline, we find that (1) “variablistic” or “covering law” models are not the dominant way of making causal claims, (2) research methods affect but do not determine causal usage, and (3) the use of explicit causal language and the concept of “mechanisms” to make causal claims is limited. Instead, we find that metaphors and metaphoric reasoning are fundamental for causal claims‐making in the discipline. On this basis, we define three dominant causal types used in sociology today, which we label the P robabilistic, I nitiating and C onditioning types. We theorize this outcome as demonstrating the primary role that cognitive models play in providing inference‐rich metaphors that allow sociologists to map causal relationships on to empirical processes.