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Abductive Coding: Theory Building and Qualitative (Re)Analysis

Author

Listed:
  • Luis Vila-Henninger
  • Claire Dupuy
  • Virginie Van Ingelgom
  • Mauro Caprioli
  • Ferdinand Teuber
  • Damien Pennetreau
  • Margherita Bussi
  • Cal Le Gall

Abstract

Qualitative secondary analysis has generated heated debate regarding the epistemology of qualitative research. We argue that shifting to an abductive approach provides a fruitful avenue for qualitative secondary analysts who are oriented towards theory-building. However, the concrete implementation of abduction remains underdeveloped—especially for coding. We address this key gap by outlining a set of tactics for abductive analysis that can be applied for qualitative analysis. Our approach applies Timmermans and Tavory's ( Timmermans and Tavory 2012 ; Tavory and Timmermans 2014 ) three stages of abduction in three steps for qualitative (secondary) analysis: Generating an Abductive Codebook, Abductive Data Reduction through Code Equations, and In-Depth Abductive Qualitative Analysis. A key contribution of our article is the development of “code equations†—defined as the combination of codes to operationalize phenomena that span individual codes. Code equations are an important resource for abduction and other qualitative approaches that leverage qualitative data to build theory.

Suggested Citation

  • Luis Vila-Henninger & Claire Dupuy & Virginie Van Ingelgom & Mauro Caprioli & Ferdinand Teuber & Damien Pennetreau & Margherita Bussi & Cal Le Gall, 2024. "Abductive Coding: Theory Building and Qualitative (Re)Analysis," Sociological Methods & Research, , vol. 53(2), pages 968-1001, May.
    • Handle: RePEc:sae:somere:v:53:y:2024:i:2:p:968-1001
    DOI: 10.1177/00491241211067508
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    References listed on IDEAS

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    1. Mettler, Suzanne, 2002. "Bringing the State Back In to Civic Engagement: Policy Feedback Effects of the G.I. Bill for World War II Veterans," American Political Science Review, Cambridge University Press, vol. 96(2), pages 351-365, June.
    2. Grimmer, Justin & Stewart, Brandon M., 2013. "Text as Data: The Promise and Pitfalls of Automatic Content Analysis Methods for Political Texts," Political Analysis, Cambridge University Press, vol. 21(3), pages 267-297, July.
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    1. Dinh, Jeannette Mai & Isaak, Andrew Jay & Yahyaoui, Yasmine, 2024. "Investing for good – Uncovering crowd investors' motivations to participate in sustainability-oriented crowdlending," Technological Forecasting and Social Change, Elsevier, vol. 207(C).

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