Disagreement is essential to scientific progress. However, the extent of disagreement in science, its evolution over time, and the fields in which it happens, remains poorly understood. Leveraging a massive collection of English-language scientific texts, we develop a cue-phrase based approach to identify instances of disagreement citations across more than four million scientific articles. Using this method, we construct an indicator of disagreement across scientific fields over the 2000-2015 period. In contrast with black-box text classification methods, our framework is transparent and easily interpretable. We reveal a disciplinary spectrum of disagreement, with higher disagreement in the social sciences and lower disagreement in physics and mathematics. However, detailed disciplinary analysis demonstrates heterogeneity across sub-fields, revealing the importance of local disciplinary cultures and epistemic characteristics of disagreement. Paper-level analysis reveals notable episodes of disagreement in science, and illustrates how methodological artifacts can confound analyses of scientific texts. These findings contribute to a broader understanding of disagreement and establish a foundation for future research to understanding key processes underlying scientific progress.
翻译:科学进步离不开分歧是科学进步的关键。然而,科学的分歧程度、其随时间演变以及发生分歧的领域仍然不易理解。利用大量英文科学文献,我们开发了一种基于导语的方法,以查明400多万篇科学文章的争议引用案例。使用这种方法,我们构建了科学领域在2000-2015年期间的分歧指标。与黑盒文本分类方法相比,我们的框架是透明和容易解释的。我们揭示了各种学科分歧,社会科学中的分歧较多,物理学和数学中的分歧较少。然而,详细的学科分析显示了各子领域的差异性,揭示了地方纪律文化的重要性和分歧的认知特征。文件层面的分析揭示了科学领域显著的分歧,并说明了方法工艺如何将科学文本分析混为一体。这些研究结果有助于更广泛地理解分歧,并为未来研究奠定基础,以了解科学进步的关键进程。