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The DOI matches its Crossref record; 22 of the 22 references it cites were found in a registry or an index.

Researching without representation? Language and materiality in post-qualitative methodology

MacLure, Maggie·2013·International Journal of Qualitative Studies in Education

Abstract

The article imagines a materially informed post-qualitative research. Focusing upon issues of language and representation, under the influence of Deleuze’s Logic of Sense, it argues for research practices capable of engaging the materiality of language itself. It proposes the development of non- or post-representational research practices, drawing on contemporary materialist work that rejects the static, hierarchical logic of representation, and practices such as interpretation and analysis as conventionally understood. The article explores the ontological and the practical implications of this state of affairs, via a re-reading of a fragment of what would have been called data. Offering relief from the ressentiment and piety that have characterised qualitative methodologists’ engagements with scientific method, the ‘post’ could therefore be read as signalling the demise of qualitative research. Or at least, as inaugurating a qualitative research that would be unrepresentable to itself.

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Metadata

Authors
MacLure, M.
Venue
International Journal of Qualitative Studies in Education
Published
2013-07
Volume
26
Issue
6
Pages
658-667
ISSN
  • 0951-8398 (ISSN-L)
  • 1366-5898
OpenAlex
W2085317071
Cited by
849
References
22
FWCI
476.25
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Researching without representation? Language and materiality in post-qualitative methodology. https://app.cochat.ai/papers/10.1080/09518398.2013.788755
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MacLure, M. (2013). Researching without representation? Language and materiality in post-qualitative methodology. International Journal of Qualitative Studies in Education. https://doi.org/10.1080/09518398.2013.788755

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.