Enhancing the robustness of causal claims based on case study research on conflict zones: observations from fieldwork in Donbas

Research output: Contribution to journalArticlepeer-review

310 Downloads (Pure)

Abstract

Focusing on process tracing and using the example of fieldwork in Donbas, I develop an argument on what theoretically grounded and empirically detailed methodological solutions can be considered to mitigate the challenges of research on conflict zones and assure the robustness of any causal claims made. I first outline my assumptions about process tracing as the central case study method and its application to research on conflict zones, and then discuss in more detail data requirements, data collection, and data analysis. Using two examples of case studies on the war in and over Donbas, I illustrate how three standards of best-practice in process tracing—the need for a theory-guided inquiry, the necessity to enhance causal inference by paying attention to (and ruling out) rival explanations, and the importance of transparency in the design and execution of research—can be applied in the challenging circumstances of fieldwork-based case studies of
conflict zones. I conclude by suggesting that as a minimum threshold for reliance upon causal inferences, these three standards also should align with a standard of evidence that requires both the theoretical and empirical plausibility of any conclusions drawn.
Original languageEnglish
JournalNationalities Papers
Early online date28 Jul 2020
DOIs
Publication statusE-pub ahead of print - 28 Jul 2020

Keywords

  • qualitative research
  • fieldwork
  • case studies
  • process tracing
  • Donbas

ASJC Scopus subject areas

  • Political Science and International Relations

Fingerprint

Dive into the research topics of 'Enhancing the robustness of causal claims based on case study research on conflict zones: observations from fieldwork in Donbas'. Together they form a unique fingerprint.

Cite this