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Evaluating research assessment: metrics-based analysis exposes implicit bias in REF2014 results

Dix, Alan (2016) Evaluating research assessment: metrics-based analysis exposes implicit bias in REF2014 results. Impact of Social Sciences Blog (22 Mar 2016). Blog Entry.

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Abstract

The recent UK research assessment exercise, REF2014, attempted to be as fair and transparent as possible. However, Alan Dix, a member of the computing sub-panel, reports how a post-hoc analysis of public domain REF data reveals substantial implicit and emergent bias in terms of discipline sub-areas (theoretical vs applied), institutions (Russell Group vs post-1992), and gender. While metrics are generally recognised as flawed, our human processes may be uniformly worse.

Item Type: Online resource (Blog Entry)
Official URL: http://blogs.lse.ac.uk/impactofsocialsciences/
Additional Information: © 2016 LSE Impact of Social Sciences © CC BY 3.0; Online
Divisions: LSE
Subjects: H Social Sciences > HC Economic History and Conditions
Q Science > QA Mathematics
Sets: Collections > Impact of Social Sciences Blog at LSE
Date Deposited: 31 May 2016 07:44
Last Modified: 03 Mar 2019 00:14
URI: http://eprints.lse.ac.uk/id/eprint/66679

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