Wright, Jessey (2019) Saving Data Analysis: Epistemic Friction and Progress in Neuroimaging Research. [Preprint]

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Abstract

Data must be manipulated for their evidential import to be assessed. However, data analysis is regarded as a source of inferential errors by scientists and critics of neuroscience alike. In this chapter I argue that of data analysis is epistemically challenged in part because data are causally separated from the events that they are intended to provide evidence for claims about. Experimental manipulations place researchers in epistemically advantageous positions by making contact with the objects and phenomena of interest. Data manipulations, on the other hand, are applied to material objects that are not in causal contact with the events they are used to learn about. I then propose that some of the inferential liabilities that go along with data manipulation are partly overcome through the occurrence of epistemic friction. I consider two forthcoming contributions to network neuroscience to illustrate the benefits, and risks, of the data analyst’s reliance on epistemic friction.

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Item Type:	Preprint
Creators:	Creators Email ORCID Wright, Jessey jwrig25@stanford.edu 0000-0001-5003-0572
Keywords:	Philosophy of Neuroscience; Network Neuroscience; Data Analysis; Data Interpretation; Inference; fMRI
Subjects:	Specific Sciences > Neuroscience > Cognitive Neuroscience General Issues > Evidence General Issues > Experimentation Specific Sciences > Neuroscience
Depositing User:	Dr Jessey Wright
Date Deposited:	24 Sep 2019 17:41
Last Modified:	24 Sep 2019 17:41
Item ID:	16456
Subjects:	Specific Sciences > Neuroscience > Cognitive Neuroscience General Issues > Evidence General Issues > Experimentation Specific Sciences > Neuroscience
Date:	2019
URI:	https://philsci-archive.pitt.edu/id/eprint/16456

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