How we load our data sets with theories and why we do so purposefully.

Citation data:

Studies in history and philosophy of science, ISSN: 0039-3681, Vol: 60, Page: 1-6

Publication Year:
2016
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Repository URL:
http://philsci-archive.pitt.edu/id/eprint/13362
PMID:
27938717
DOI:
10.1016/j.shpsa.2016.08.002
Author(s):
Rochefort-Maranda, Guillaume
Publisher(s):
Elsevier BV
Tags:
Arts and Humanities
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article description
In this paper, I compare theory-laden perceptions with imputed data sets. The similarities between the two allow me to show how the phenomenon of theory-ladenness can manifest itself in statistical analyses. More importantly, elucidating the differences between them will allow me to broaden the focus of the existing literature on theory-ladenness and to introduce some much-needed nuances. The topic of statistical imputation has received no attention in philosophy of science. Yet, imputed data sets are very similar to theory-laden perceptions, and they are now an integral part of many scientific inferences. Unlike the existence of theory-laden perceptions, that of imputed data sets cannot be challenged or reduced to a manageable source of error. In fact, imputed data sets are created purposefully in order to improve the quality of our inferences. They do not undermine the possibility of scientific knowledge; on the contrary, they are epistemically desirable.

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