Sample representation in the social sciences

Synthese (10):9097-9115 (2021)
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The social sciences face a problem of sample non-representation, where the majority of samples consist of undergraduate students from Euro-American institutions. The problem has been identified for decades with little trend of improvement. In this paper, I trace the history of sampling theory. The dominant framework, called the design-based approach, takes random sampling as the gold standard. The idea is that a sampling procedure that is maximally uninformative prevents samplers from introducing arbitrary bias, thus preserving sample representation. I show how this framework, while good in theory, faces many challenges in application. Instead, I advocate for an alternative framework, called the model-based approach to sampling, where representative samples are those balanced in composition, however they were drawn. I argue that the model-based framework is more appropriate in the social sciences because it allows for systematic assessment of imperfect samples and methodical improvement in resource-limited scientific contexts. I end with practical proposals of improving sample quality in the social sciences.

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Kino Zhao
Simon Fraser University

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Calibrating statistical tools: Improving the measure of Humanity's influence on the climate.Corey Dethier - 2022 - Studies in History and Philosophy of Science Part A 94 (C):158-166.
Prior Information in Frequentist Research Designs: The Case of Neyman’s Sampling Theory.Adam P. Kubiak & Paweł Kawalec - 2022 - Journal for General Philosophy of Science / Zeitschrift für Allgemeine Wissenschaftstheorie 53 (4):381-402.

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