NDLI: From Correlation to Causation: What Do We Need in the Historical Sciences?

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From Correlation to Causation: What Do We Need in the Historical Sciences?

Content Provider	Springer Nature Link
Author	Ebach, Malte C. Michael, Michaelis S.
Copyright Year	2016
Abstract	Changes in the methodology of the historical sciences make them more vulnerable to unjustifiable speculations being passed off as scientific results. The integrity of historical science is in peril due the way speculative and often unexamined causal assumptions are being used to generate data and underpin the identification of correlations in such data. A step toward a solution is to distinguish between plausible and speculative assumptions that facilitate the inference from measured and observed data to causal claims. One way to do that is by comparing these assumptions against a well-attested set of aspects of causation, such as the so-called “Bradford Hill Criteria” (BHC). The BHC do not provide a test for causation or necessary and sufficient conditions for causation but do indicate grounds for further investigation. By revising the BHC to reflect the needs and focus of historical sciences, it will be possible to assess the cogency of methods of investigation. These will be the Historical Sciences Bradford Hill Criteria (HSBHC). An application to one area in historical science is used to demonstrate the effectiveness of the HSBHC, namely biogeography. Four methods are assessed in order to show how the HSBHC can be used to examine the assumptions between our data and the causal biogeographical processes we infer.
Starting Page	241
Ending Page	262
Page Count	22
File Format	PDF
ISSN	00015342
Journal	Acta Biotheoretica
Volume Number	64
Issue Number	3
e-ISSN	15728358
Language	English
Publisher	Springer Netherlands
Publisher Date	2016-06-30
Publisher Place	Dordrecht
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Biogeography Data Evidence Historical Sciences Bradford Hill Criteria Phylogenetics Philosophy of Biology Evolutionary Biology
Content Type	Text
Resource Type	Article
Subject	Philosophy Applied Mathematics Medicine Biochemistry, Genetics and Molecular Biology Environmental Science Agricultural and Biological Sciences

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