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Analysing Language, Sex and Age in a Corpus of Patient Feedback - A Comparison of Approaches (Paperback) Loot Price: R617
Discovery Miles 6 170
Analysing Language, Sex and Age in a Corpus of Patient Feedback - A Comparison of Approaches (Paperback): Paul Baker, Gavin...

Analysing Language, Sex and Age in a Corpus of Patient Feedback - A Comparison of Approaches (Paperback)

Paul Baker, Gavin Brookes

Series: Elements in Corpus Linguistics

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Loot Price R617 Discovery Miles 6 170 | Repayment Terms: R58 pm x 12*

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This Element explores approaches to locating and examining social identity in corpora with and without the aid of demographic metadata. This is a key concern in corpus-aided studies of language and identity, and this Element sets out to explore the main challenges and affordances associated with either approach and to discern what either approach can (and cannot) show. It describes two case studies which each compare two approaches to social identity variables - sex and age - in a corpus of 14-million words of patient comments about NHS cancer services in England. The first approach utilises demographic tags to group comments according to patients' sex/age while the second involves categorising cases where patients disclose their sex/age in their comments. This Element compares the findings from either approach, with the approaches themselves being critically discussed in terms of their implications for corpus-aided studies of language and identity.

General

Imprint: Cambridge UniversityPress
Country of origin: United Kingdom
Series: Elements in Corpus Linguistics
Release date: July 2022
Authors: Paul Baker • Gavin Brookes
Dimensions: 228 x 151 x 5mm (L x W x T)
Format: Paperback - Trade
Pages: 75
ISBN-13: 978-1-00-901377-2
Categories: Books > Language & Literature > Language & linguistics > Sociolinguistics
Books > Language & Literature > Language & linguistics > Computational linguistics
Books > Language & Literature > Language & linguistics > Semantics (meaning) > General
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LSN: 1-00-901377-7
Barcode: 9781009013772

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