How has the credibility revolution reshaped political science? We address this question by using a large language model to classify 91,632 articles published between 2003 and 2023 across 174 political science journals, focusing on causal research designs, transparency practices, and citation patterns. Design-based studies -- research strategies that explicitly a research design and the assumptions required for causal identification -- have become increasingly common, displacing regression-based analyses that rely primarily on modeling assumptions. Yet as of 2023, studies without an explicit identification strategy still constitute nearly 40% of empirical quantitative work. Within design-based research, survey experiments dominate, while field experiments and quasi-experimental approaches have grown more modestly. Transparency practices such as placebo tests and power analysis remain rare. Design-based studies are concentrated in top journals and among authors at highly ranked institutions, and enjoy a persistent citation premium. The credibility revolution has meaningfully reshaped the discipline, though unevenly and incompletely.

翻译：可信度革命如何重塑了政治学？我们通过使用大语言模型对2003年至2023年间发表在174种政治学期刊上的91,632篇文章进行分类来探讨这个问题，重点关注因果研究设计、透明度实践和引文模式。基于设计的研究——即明确阐述研究设计及因果识别所需假设的研究策略——已变得越来越普遍，取代了主要依赖建模假设的回归分析。然而截至2023年，没有明确识别策略的研究仍占实证定量工作的近40%。在基于设计的研究中，调查实验占主导地位，而实地实验和准实验方法的增长则较为有限。诸如安慰剂检验和功效分析等透明度实践仍然罕见。基于设计的研究主要集中在顶级期刊和顶尖机构的作者中，并享有持续的引文溢价。可信度革命已显著重塑了该学科，尽管这种重塑并不均衡且不彻底。