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“Explain” in scientific discourse

Abstract

The philosophical literature on scientific explanation contains a striking diversity of accounts. I use novel empirical methods to address this fragmentation and assess the importance and generality of explanation in science. My evidence base is a set of 781 articles from one year of the journal Science, and I begin by applying text mining techniques to discover patterns in the usage of “explain” and other words of philosophical interest. I then use random sampling from the data set to develop and test a classification scheme for scientific explanation. My results show that explanation and inference to the best explanation are ubiquitous in science, that they occur across a wide range of scientific disciplines, and that they are a goal of scientific practise. These explanations and inferences to the best explanation come in a diversity forms, which at least partially justifies the fragmentation of philosophical accounts. I draw two methodological lessons: first that text mining can enhance traditional conceptual analysis by establishing facts about word usage; and second that random sampling of cases can increase our confidence that a philosophical account applies in general. These empirical techniques supplement traditional philosophical methods.

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Correspondence to James A. Overton.

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Overton, J.A. “Explain” in scientific discourse. Synthese 190, 1383–1405 (2013). https://doi.org/10.1007/s11229-012-0109-8

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Keywords

  • Philosophy of science
  • Explanation
  • Text mining
  • Methodology