Anglia Ruskin Research Online (ARRO)
Browse
Smith_Daniel_2015.doc (94.5 kB)

The Gent-rification of English masculinities: class, race and nation in contemporary consumption

Download (94.5 kB)
journal contribution
posted on 2023-08-30, 15:23 authored by Daniel R. Smith
The figure of the English gentleman is regaining traction in British society. This retrograde celebration of a type of masculinity articulating various intersections in class, racial and national identity provides not just a reliable identity-complex for contemporary British males but also imaginative solutions to the current cultural predicaments – notably, how to be English/British in the era of globalisation. This article will unpack this reformation of the gentleman and its paradoxical appearance and position at present through two consumer objects: clothing and cars. By first conceptually outlining the national, class and racialised background of the ‘gentleman’ for the British cultural imagination, the article will proceed to analyse Jack Wills’ clothing aesthetic and the recent Jaguar F-Type coupe, ‘Good to be Bad’, adverts. The article draws upon Lévi-Strauss and Jameson to conceptualise this paradoxical, mythical resurgence of gentry/gentlemanliness. By focusing on how two artefacts utilise an Americanised mythical narrative of Britishness, I claim the contemporary landscape sees the oxymoronic return of an archaic character-type refigured in a manner appropriate for an increasingly plural, multi-cultural global landscape.

History

Refereed

  • Yes

Volume

20

Issue number

4-5

Page range

391-406

Publication title

Social Identities

ISSN

1363-0296

Publisher

Taylor & Francis

File version

  • Accepted version

Language

  • eng

Legacy posted date

2018-06-22

Legacy creation date

2018-06-20

Legacy Faculty/School/Department

ARCHIVED Faculty of Arts, Law & Social Sciences (until September 2018)

Usage metrics

    ARU Outputs

    Categories

    No categories selected

    Exports

    RefWorks
    BibTeX
    Ref. manager
    Endnote
    DataCite
    NLM
    DC