Analysing Language, Sex and Age in a Corpus of Patient Feedback
A Comparison of Approaches

This Element compares qualitative and quantitative approaches to analysing patient feedback about cancer care in terms of sex and age.

Paul Baker (Author), Gavin Brookes (Author)

9781009013772, Cambridge University Press

Paperback / softback, published 21 July 2022

75 pages
22.8 x 15.1 x 0.5 cm, 0.146 kg

'… designed to meet the needs of researchers, teachers, and students who want to keep up with the changing field … Baker and Brookes' groundbreaking book on language and identity is a valuable addition to the existing literature. It highlights language to use with advances in sociodemographic information and corpus-aided studies. The book is highly systematic, not only introducing major concepts but also contributing profound commentary and in-depth explanations regarding two different approaches and research methods of great importance.' Qiuying Zhao, International Journal of Communication

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.

1. Introduction
2. Patient sex
3. Patient age
4. Conclusion and reflections
References.

Subject Areas: Computational linguistics [CFX], Semantics, discourse analysis, etc [CFG], Sociolinguistics [CFB]