A Call to Embrace Uncertainty: Rethinking Statistical Inference in Migration Research

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Abstract

This paper urges for a reevaluation of current methodologies in migration research, advocat-ing for tools that explicitly integrate uncertainty as a substantive element in the modeling process rather than as a byproduct of estimates. Specifically, it challenges the conventional application of frequentist statistical methods in migration research, emphasizing their limi-tations in expressing uncertainty and incorporating prior knowledge. From an epistemolog-ical perspective the paper highlights the limitations of traditional tools concerning what knowledge can be produced —the compression of likelihood of hypotheses— and how knowledge is produced —the consequences of relegating prior knowledge to a secondary role in analysis. The paper simultaneously motivates the need to expand tools available for statistical inference by highlighting the latent implications that the choice of method can have on the efficacy of migration research, motivated by literature on the philosophy of sci-ence and drawing concrete examples from migration governance.

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