Abstract
Are causal explanations (e.g., “she switched careers because of the COVID pandemic”) treated differently from the corresponding claims that one factor caused another (e.g., “the COVID pandemic caused her to switch careers”)? We examined whether explanatory and causal claims diverge in their responsiveness to two different types of information: covariation strength and mechanism information. We report five experiments with 1,730 participants total, showing that compared to judgments of causal strength, explanatory judgments tend to be more sensitive to mechanism and less sensitive to covariation – even though explanatory judgments respond to both types of information. We also report exploratory comparisons to judgments of understanding, and discuss implications of our findings for theories of explanation, understanding, and causal attribution. These findings shed light on the potentially unique role of explanation in cognition.
Funder
John Templeton Foundation
James S. McDonnell Foundation
Reference63 articles.
1. The role of mechanism beliefs in causal reasoning;Ahn;Explanation and Cognition,2002
2. The role of covariation versus mechanism information in causal attribution.;Ahn;Cognition,1995
3. Puerperal group A streptococcal infection: beyond Semmelweis.;Anderson;Obstetr. Gynecol.,2014
4. Medicine in stamps-Ignaz Semmelweis and Puerperal Fever.;Ataman;J. Turk. Ger. Gynecol. Assoc.,2013
5. Explanation: a mechanist alternative.;Bechtel;Stud. Hist. Philos. Biol. Biomed. Sci.,2005
Cited by
1 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献
1. Defining and developing data literacy;Routledge Open Research;2023-10-24