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.

中文翻译：

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探索不确定性、情绪和科学话语在 COVID-19 大流行期间的作用

本文探讨了加拿大魁北克省制定 COVID-19 政策时不确定性、情绪和科学话语之间的相互作用。通过应用自然语言处理（NLP）技术，开发了指数来衡量政策制定者的不确定性情绪、负面情绪以及科学陈述的流行程度。研究表明，虽然不确定情绪导致采取严格的政策，但科学陈述及其传达的证据与放松此类政策有关，因为它们提供了保证并减轻了负面情绪。此外，研究结果表明，科学陈述仅在高度不确定性的情况下才会鼓励采取更严格的政策。这项研究有助于从理论上理解健康危机决策中情绪和认知动态之间的相互作用。它强调需要细致入微地了解如何在面临不确定性的情况下使用科学，尤其是在民主进程被搁置的情况下。从方法论上来说，它展示了 NLP 在政策分析中的潜力。