ABSTRACT

It is generally accepted among philosophers of science that hypothesis testing (or confirmation) is a key methodological feature of science. As far as philosophical theories of confirmation are concerned, some emphasize the role of deduction in confirmation (e.g. the H-D method), whereas others emphasize the role of induction in confirmation (e.g. Bayesian theories of confirmation). The aim of this paper is to contribute to our understanding of scientific confirmation (or hypothesis testing) in scientific practice by taking an empirical approach. I propose that it would be illuminating to learn how practicing scientists describe their methods when they test hypotheses and/or theories. I use the tools of data science and corpus linguistics to study patterns of usage in a large corpus of scientific publications mined from the JSTOR database. Overall, the results of this empirical survey suggest that there is an emphasis on mostly the inductive aspects of confirmation in the life sciences and the social sciences, but not in the physical and the formal sciences. The results also point to interesting and significant differences between the scientific subjects within these disciplinary groups that are worth investigating in future studies.

摘要

科学哲学家普遍接受假设检验（或确认）是科学的关键方法论特征。就确认的哲学理论而言，有些强调推论在确认中的作用（例如HD方法），而另一些则强调归纳在确认中的作用（例如贝叶斯确认理论）。本文的目的是通过采用经验方法来帮助我们理解科学实践中的科学确认（或假设检验）。我认为，学习实践中的科学家在检验假设和/或理论时如何描述其方法将具有启发性。我使用数据科学和语料库语言学的工具来研究来自JSTOR数据库的大量科学出版物中的用法模式。全面的，这项实证调查的结果表明，生命科学和社会科学主要侧重于确认的归纳方面，而物理科学和形式科学则没有重点。结果还指出，这些学科组中的科学学科之间存在有趣而显着的差异，值得在以后的研究中进行研究。