Candidate knowledge? Exploring epistemic claims in scientific writing:a corpus-driven approach

Abstract

In this article I argue that the study of the linguistic aspects of epistemology has become unhelpfully focused on the corpus-based study of hedging and that a corpus-driven approach can help to improve upon this. Through focusing on a corpus of texts from one discourse community (that of genetics) and identifying frequent tri-lexical clusters containing highly frequent lexical items identified as keywords, I undertake an inductive analysis identifying patterns of epistemic significance. Several of these patterns are shown to be hedging devices and the whole corpus frequencies of the most salient of these, candidate and putative, are then compared to the whole corpus frequencies for comparable wordforms and clusters of epistemic significance. Finally I interviewed a ‘friendly geneticist’ in order to check my interpretation of some of the terms used and to get an expert interpretation of the overall findings. In summary I argue that the highly unexpected patterns of hedging found in genetics demonstrate the value of adopting a corpus-driven approach and constitute an advance in our current understanding of how to approach the relationship between language and epistemology.

Publication DOI: https://doi.org/10.3366/cor.2017.0127
Divisions: ?? 53981500Jl ??
College of Business and Social Sciences > School of Social Sciences & Humanities > Centre for Language Research at Aston (CLaRA)
College of Business and Social Sciences > Aston Institute for Forensic Linguistics
College of Business and Social Sciences > School of Social Sciences & Humanities
Additional Information: The article has been accepted for publication by Edinburgh University Press in the journal Corpora at https://www.euppublishing.com/doi/10.3366/cor.2017.0127
Uncontrolled Keywords: epistemology,hedging,corpus-driven,collocation,concordance,genetics
Full Text Link:
Related URLs: https://www.eup ... 6/cor.2017.0127 (Publisher URL)
PURE Output Type: Article
Published Date: 2017-11-01
Accepted Date: 2016-04-01
Authors: Plappert, Garry L

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