Causal Comparability, Causal Generalizations, and Epistemic Homogeneity

Runhardt, Rosa W.

doi:10.1177/0048393116681079

Cited by 4 publications

(2 citation statements)

References 16 publications

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“…Although this is a practical rather than conceptual limitation, it is sometimes a very serious limitation. Moreover, there is a related conceptual problem: In some disciplines (particularly in the social sciences), it can be argued that it is always possible to divide the population into more fine-grained reference classes based on some possible relevant features (Runhardt 2017). However, to do any statistical research, we must commit ourselves to some division of reference classes before assessing any mechanism.…”

Section: Taxonomic Incommensurabilitymentioning

confidence: 99%

Triangulation, incommensurability, and conditionalization

Liron,

Nissan-Rozen

2024

Philos. sci.

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We present a new justification for Methodological Triangulation (MT), the practice of using different methods to support the same scientific claim. Unlike existing accounts, our account captures cases in which the different methods in question are associated with, and relies on, incommensurable theories. Using a non-standard Bayesian model, we show that even in such cases, a commitment to the minimal form of epistemic conservatism, captured by the rigidity condition that stands at the basis of Jeffrey’s conditionalization, supports the practice of MT.

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Section: Taxonomic Incommensurabilitymentioning

confidence: 99%

Triangulation, incommensurability, and conditionalization

Liron,

Nissan-Rozen

2024

Philos. sci.

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“…Whereas conceptualizations provide a meaningful framing that includes possible kinds of generalization as well as the (at least implicit) aims which generalizations are meant to answer to, methods of generalization consist in specific strategies that researchers may use to make and justify generalizability claims. Various methodological frameworks for generalization, varying in precision and specificity, have been proposed (e.g., Leviton, 2015; Payne & Williams, 2005; Polit & Beck, 2010; Mayring, 2007; Runhardt, 2017). Perhaps not surprisingly, explicit proposals for such strategies are more often encountered within qualitative research discourse than in scientific discourse more broadly, likely due in large part to the contested nature of generalization within qualitative research.…”

Section: Generalizations In Scientific Discoursementioning

confidence: 99%

Scientific generalization in psychological inquiry: A concept in need of clarification.

Slaney¹,

Tafreshi²

2021

Qualitative Psychology

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Although generalization is typically described in the methodological literature as both a goal and achievement within quantitative research traditions, qualitative research is often presumed to be incapable of and, in some cases, unconcerned with generalization. However, the concept of generalization is much less bounded than it might appear at first blush. In fact, it has multiple senses and applications, some of which are more applicable in some areas of research than in others. In this article, we present a conceptual analysis of generalization and related concepts. We begin with an analysis of ordinary language uses and then move to more "technical" uses within scientific discourse. We highlight accounts given in the general philosophy of science literature as well as prescribed and actual uses in psychological research within domains in which quantitative and qualitative methods, respectively, have historically been privileged. Finally, drawing from the different kinds of generalizations that feature within and across quantitative and qualitative research, we sketch some points that researchers might keep in mind when considering whether and how generalization plays out in their research.

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Concrete Counterfactual Tests for Process Tracing: Defending an Interventionist Potential Outcomes Framework

Runhardt

2022

Sociological Methods & Research

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This article uses the interventionist theory of causation, a counterfactual theory taken from philosophy of science, to strengthen causal analysis in process tracing research. Causal claims from process tracing are re-expressed in terms of so-called hypothetical interventions, and concrete evidential tests are proposed which are shown to corroborate process tracing claims. In particular, three steps are prescribed for an interventionist investigation, and each step in turn is shown to make the causal analysis more robust, amongst others by disambiguating causal claims and clarifying or strengthening the existing methodological advice on counterfactual analysis. The article's claims are then illustrated using a concrete example, Haggard and Kaufman's analysis of the Argentinian transition to democracy. It is shown that interventionism could have strengthened the authors’ conclusions. The article concludes with a short Bayesian analysis of its key methodological proposals.

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Causal Comparability, Causal Generalizations, and Epistemic Homogeneity

Cited by 4 publications

References 16 publications

Triangulation, incommensurability, and conditionalization

Triangulation, incommensurability, and conditionalization

Scientific generalization in psychological inquiry: A concept in need of clarification.

Concrete Counterfactual Tests for Process Tracing: Defending an Interventionist Potential Outcomes Framework

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