Abstract
Abstract This article examines the interplay between uncertainty, emotions, and scientific discourse in shaping COVID-19 policies in Quebec, Canada. Through the application of natural language processing (NLP) techniques, indices were developped to measure sentiments of uncertainty among policymakers, their negative sentiments, and the prevalence of scientific statements. The study reveals that while sentiments of uncertainty led to the adoption of stringent policies, scientific statements and the evidence they conveyed were associated with a relaxation of such policies, as they offered reassurance and mitigated negative sentiments. Furthermore, the findings suggest that scientific statements encouraged stricter policies only in contexts of high uncertainty. This research contributes to the theoretical understanding of the interplay between emotional and cognitive dynamics in health crisis policymaking. It emphasizes the need for a nuanced understanding of how science may be used in the face of uncertainty, especially when democratic processes are set aside. Methodologically, it demonstrates the potential of NLP in policy analysis.
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