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 largely unknown. Leveraging a massive collection of 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 artefacts 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在很大程度上仍不为人所知。利用大量科学文本,我们开发了一种基于提示的手语方法,以查明400多万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不同,我们的框架是透明和容易解释的。我们揭示了各种学科的分歧,社会科学中的分歧较高,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分领域的差异性,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,并展示了方法工艺如何混淆科学文本分析。这些发现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。