Searching for a middle ground? A spectrum of views of causality in qualitative research

Abstract

Qualitative scholars exhibit a wide range of views on and approaches to causality. While some approaches reject causality from the outset, a large strand of qualitative research in political science and international relations does, however, pursue causal explanation. Qualitative scholars nevertheless disagree about what causality means. Our paper reviews what causality means within different strands of qualitative research and how qualitative scholars engage in causal explanations. We focus particular attention on the fertile middle ground between qualitative research that seeks to mimic the statistical model and research that rejects causality entirely. In broad strokes, we understand views of causality as lying on a spectrum and partly overlapping. Along the spectrum, we identify three main clusters: ‘positivist leaning,’ ‘postpositivist leaning,’ and ‘interpretivist leaning.’ Within each cluster, we identify the main traits and provide illustrative examples. We find merit in each of these three clusters of approaches and in the ongoing dialogue among qualitative scholars of different orientations. Understanding similarities and differences in the way various scholars address causality might encourage some to take steps along the spectrum and expand their repertoires to embrace elements of other approaches. By making these distinctions more explicit, we hope to be able to enhance our understanding of different views of causality and the extent to which they overlap and provide the potential for collaboration.

Exploring the link between administrative styles and policy output: The case of the Italian Extraordinary Commissioner for the Covid‐19 Emergency

“…Based on this empirical analysis, and to reinforce the validity of the qualitative study (Ruffa & Evangelista, 2021), the data analysis procedure has been based on a triangulation of the primary and secondary data collected. To this aim, a four-step data analysis procedure has been carried out.…”

Systematic, quality appraisal of household recycling influences research finds evidence is mostly insufficient

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“…Exploring and establishing temporal precedence for key factorsfor example through carefully selected research designs (see Table 1 note i), or by building explicit probing of temporality into self-reporting (e.g. Ruffa & Evangelista, 2021).…”

“…what would have happened in the absence of the influence) for example through appropriate research designs, or in cross-sectional self-report data by including explicit counterfactual questions or probing for counterfactual evidence (e.g. Ruffa & Evangelista, 2021;Saladié & Santos-Lacueva, 2016).…”