Jul 2026· International Political Science Review· 1 citation· 32 references
Abstract
Political science is undergoing a pronounced methodological shift toward causal identification and design-based inference, increasingly marginalizing qualitative and observational approaches. We argue that this shift rests on the flawed premise that methods can be ranked in the abstract, independently of the research question and the theories at stake. Drawing on a Popperian understanding of scientific progress, we develop a framework of comparative theory testing in which method choice is derived from the competing theories themselves. When rival theories generate observationally non-equivalent implications—causal, correlational, or descriptive—any form of evidence capable of adjudicating between them has epistemic standing. This grounds methodological pluralism not in a normative appeal for inclusivity, but in the internal logic of rigorous theory testing. We illustrate the framework through canonical examples, propose criteria for evaluating the rigor of comparative theory tests, and show that design-based methods earn their place within—not above—this framework. The result is a unified perspective that preserves our capacity to engage big-picture questions while maintaining the standards of falsifiability and theoretical precision that scientific inquiry requires.
ABSTRACT Despite the consolidation of experimental designs as a central standard for causal inference in adjacent fields, experiments remain peripheral in large segments of management research. This article argues that such marginalization is not primarily technical, but epistemic and institutional. It reconstructs six recurrent objections - complexity, external validity, feasibility, theory reduction, non-manipulability, and ethical scope - that structure skepticism toward experimentation and shows how they normalize the substitution of statistical sophistication for design-based identification. The analysis suggests that resistance to experiments reflects entrenched evaluative norms about what counts as rigor and relevance, rather than demonstrated methodological inadequacy. To move beyond dichotomous debates, the article introduces a simple evaluative framework structured along two dimensions: causal ambition and organizational embeddedness. By conceptualizing experimentation as a continuum, the framework aligns the strength of causal claims with the inferential capacities of different designs, making trade-offs explicit rather than implicit. The central contribution is disciplinary rather than technical: repositioning experimentation as a reference point for transparent causal reasoning. The article concludes by calling for greater alignment between causal claims and research design, emphasizing inferential discipline as a condition for credible knowledge in management research.
João Fernandes Jorge de Siqueira, R. Porto, Jonathan Simões Freitas· BAR: Brazilian Administratio...· 0 citations
This paper critically reassesses the epistemic relationship between religion and science,
examining whether they function as competitors, allies, or differentiated yet complementary
domains of inquiry. It situates the discussion historically, demonstrating that episodes of
tension often reflect disputes over authority rather than evidence alone. The analysis
distinguishes methodological constraint from ontological assertion, showing that reductionist
claims—whether scientistic or theological—overextend their warrant and obscure the distinct
roles of moral reasoning, metaphysical reflection, and existential interpretation. Science is
shown to govern empirical explanation through methodological naturalism, testability, and
predictive reliability, while religion advances cognitive, normative, and existential claims that
resist exhaustive empirical verification but remain subject to rational assessment. The paper
critiques reductionism on three fronts: internal coherence, normativity, and the limits of third
person explanation in consciousness studies, revealing persistent gaps in scientistic
exclusivism. In response, it develops a calibrated complementary model grounded in epistemic
autonomy, conditional intersection, and regulated convergence. The model reframes apparent
conflict as domain misalignment rather than intrinsic opposition, preserving methodological
integrity while enabling principled interaction. Implications for public reason, education, and
policy formation are considered, emphasizing the disciplined coexistence of plural epistemic
authorities. By clarifying the boundaries, intersections, and mutual constraints of science and
religion, the paper contributes a context-sensitive framework for navigating contemporary
intellectual, moral, and metaphysical challenges without collapsing inquiry into a single
method or insulating domains from engagement. (226 words)
Gabriel Adedayo Idogbe· International Journal of Rel...· 0 citations
Gailmard (2026) and Dowding and Miller (2026) draw attention to a methodological gap that political science has yet to adequately address: causal identification, on its own, does not constitute causal explanation. Both contributions help clarify the gap. We extend their analyses in three ways. First, we identify three places where Gailmard’s framework relies on conceptual commitments that operate implicitly within his formal apparatus. The coherence equivalence used in his proofs is stronger than the three coherence properties he states; the bundle reading of theoretical models gives Proposition 5 its content but imposes a tolerance condition that the framework does not address; and Proposition 6 on generalization supplies a necessary-and-sufficient condition for generalization without specifying when that condition obtains. Second, we extend Dowding and Miller’s explanatory pluralism by locating constitutive explanation and explanation by constraint within a structured inferential framework, and we argue that equilibrium explanation comes in distinct varieties — equifinality and comparative statics — that play different roles in political science formal theory. Third, we introduce a nested modeling framework that separates three levels — data, conceptual model, and theory — clarifying how identification, non-causal explanation, and theoretical inference jointly support causal knowledge.
Dwayne Woods· Chinese Political Science Re...· 0 citations
It is argued that demonstrating internal incoherence is a necessary precursor to AI alignment as well as a broader phenomenon of epistemic instability in generative AI wherein models fail to reliably maintain coherence with respect to their own prior outputs.
Pegah Nokhiz, Aravinda Kanchana Ruwanpathirana, Helen Nissenbaum· 0 citations
Big data and empirical social science share an often-subterraneous assumption, namely, positivism. Some of their jointly hidden premises are that experiences, preferences, and culture are all equally quantifiable, testable, and measurable. Further, their view is a reification of the status quo, a harmonistic view of society. On the other hand, the critical view espouses
social antagonism
, the view that society essentially consists of a struggle between groups. Critical theory argues against the critical rationalists that positivism (and thus, empirical social science) is guilty of a political agnosticism and, therefore, services the ends of bureaucracy and administration. This paper draws out some latent beliefs of big data as a new version of positivism and shows that big data inherits the problems of empirical social science. In particular, algorithms and data analytics for predictive policing, aggressively personalized advertisement, and prison recidivism stand out as substantial evidence of the new positivism that surges in administered society.
Andrew Burnside· Philosophy & Social Crit...· 0 citations
This paper argues that debates over saturation in qualitative research point to a deeper problem than conceptual ambiguity or inconsistent application. At stake is the lack of a general account of how inquiry becomes sufficient. Drawing on sociological theories of justification, evaluation, and boundary work, the paper introduces the concept of epistemic closure to describe how qualitative inquiry is rendered sufficiently complete to warrant stopping, despite the continued availability of further data and alternative interpretations. Reframing saturation in these terms shifts attention from methodological endpoints to the social processes through which claims of adequacy are rendered credible. The paper develops a typology of four distinct grammars of closure—redundancy, interpretive, procedural, and audit—and argues that contemporary alternatives to saturation are best understood as different ways of rendering inquiry sufficiently complete rather than as competing stopping criteria. In doing so, it reinterprets contemporary debates over saturation, information power, and rigor as struggles over how closure is achieved. The paper concludes by showing how this framework recasts rigor as a relational and situated accomplishment while situating epistemic closure within the broader governance of qualitative knowledge.
Michael S. Carolan· Sociological inquiry· 0 citations
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