认识论
推论
杠杆(统计)
口译(哲学)
意义(存在)
背景(考古学)
计算机科学
科学哲学
批评
特权(计算)
社会学
数据科学
人工智能
哲学
法学
政治学
古生物学
生物
程序设计语言
计算机安全
作者
Sandeep Pillai,Brent Goldfarb,David A. Kirsch
摘要
Abstract Research Summary Many strategy studies implicitly rely upon inference to the best explanation (IBE) or modern abduction. We leverage recent work in the philosophy of science to consider how we arrive at “best” explanations, explanations that are lovely, in the sense that they are useful, general, and provide meaning, and likely, in the sense that they are close to the truth. Interpretation of observational results requires an understanding of context that statistical analysis alone cannot provide. At that point of encounter, historical methods—hermeneutics, contextualization and source criticism—can improve IBE by helping scholars (1) generate new candidate explanations and (2) systematically judge, privilege, and balance the explanatory virtues that constitute the loveliness and likeliness of explanations. Managerial Summary Many strategy studies iteratively use data and theory to inference to the best explanation of observed phenomena. We leverage recent work in the philosophy of science to consider how we arrive at best explanations that are useful, general, provide meaning, and, at the same time, are close to the truth. Interpreting observational results requires an understanding of the context that statistical analysis alone cannot provide. At that point of encounter, methodological tools from the field of history can improve the process of determining the best explanation by helping scholars (1) generate new candidate explanations and (2) systematically judge and privilege explanations.
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