The transparency of quantitative empirical legal research published in highly ranked law journals (2018–2020): an observational study [version 2; peer review: 3 approved]

Sarah Schiavone, Alex Holcombe, Ruby Bishop,Simine Vazire,Natali Dilevski, Rosemary Gatfield-Jeffries,Jason Chin,Kathryn Zeiler

F1000Research(2024)

引用 0|浏览1
暂无评分
摘要
Background Scientists are increasingly concerned with making their work easy to verify and build upon. Associated practices include sharing data, materials, and analytic scripts, and preregistering protocols. This shift towards increased transparency and rigor has been referred to as a “credibility revolution.” The credibility of empirical legal research has been questioned in the past due to its distinctive peer review system and because the legal background of its researchers means that many often are not trained in study design or statistics. Still, there has been no systematic study of transparency and credibility-related characteristics of published empirical legal research. Methods To fill this gap and provide an estimate of current practices that can be tracked as the field evolves, we assessed 300 empirical articles from highly ranked law journals including both faculty-edited journals and student-edited journals. Results We found high levels of article accessibility (86%, 95% CI = [82%, 90%]), especially among student-edited journals (100%). Few articles stated that a study’s data are available (19%, 95% CI = [15%, 23%]). Statements of preregistration (3%, 95% CI = [1%, 5%]) and availability of analytic scripts (6%, 95% CI = [4%, 9%]) were very uncommon. (i.e., they collected new data using the study’s reported methods, but found results inconsistent or not as strong as the original). Conclusion We suggest that empirical legal researchers and the journals that publish their work cultivate norms and practices to encourage research credibility. Our estimates may be revisited to track the field’s progress in the coming years.
更多
查看译文
关键词
metaresearch,open science,transparency,credibility,empirical legal research,eng
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要