My claim is that in many investigations, principled computerized search is invaluable for reliable, generalizable, informative, scientific inquiry. The main thesis of my talk is that, in the spirit and letter of Mayo's and Spanos’ notion of severe testing, modern computational algorithms that search data for causal relations severely test their resulting models in the process of "constructing" them. Notwithstanding, "data dredging" is routinely practiced in the human sciences using "traditional" methods-various forms of regression for example. Nowadays, "data dredging"-using data to bring hypotheses into consideration and regarding that same data as evidence bearing on their truth or falsity-is widely denounced by both philosophical and statistical methodologists. ABSTRACT: "Data dredging"-searching non experimental data for causal and other relationships and taking that same data to be evidence for those relationships-was historically common in the natural sciences-the works of Kepler, Cannizzaro and Mendeleev are examples.
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