The DOI matches its Crossref record.
Student Attitudes, Image and the Gender Gap
Abstract
ABSTRACT This article, based on a 3 year study in East Anglian schools, draws on a range of evidence pointing to different attitudes of girls and boys to General Certificate of Secondary Education (GCSE) work. Suggestions are made to account for these differences, with particular emphasis being placed on peer pressure, image and social groupings. Although these are relevant to both sexes, it was found to be more acceptable for girls to work hard and still be part of the ‘in crowd’, whilst boys were under greater pressure to conform to a ‘cool’, masculine image, and were more likely to be ridiculed for working hard. The article concludes by suggesting that one approach to closing the current gender gap may be to enable boys in school to move beyond the stereotypical image of the macho male.
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Citations
Cited by
Rothon, C., Head, J., Clark, C., Klineberg, E., Cattell, V., & Stansfeld, S. (2009) · Social Psychiatry and Psychiatric Epidemiology · doi:10.1007/s00127-008-0452-8 · Cited by 104
Choosing music: exploratory studies into the low uptake of music GCSE
Lamont, A., & Maton, K. (2008) · British Journal of Music Education · doi:10.1017/s0265051708008103 · Cited by 103
Syväoja, H. J., Kankaanpää, A., Kallio, J., Hakonen, H., Kulmala, J., Hillman, C. H., Pesonen, A.-K., & Tammelin, T. H. (2018) · Journal of Physical Activity and Health · doi:10.1123/jpah.2017-0135 · Cited by 50
Metadata
- Authors
- Warrington, M., Younger, M., & Williams, J.
- Venue
- British Educational Research Journal
- Publisher
- Wiley
- Published
- 2000-06
- Volume
- 26
- Issue
- 3
- Pages
- 393-407
- ISSN
- 0141-1926 (ISSN-L)
- 1469-3518
- OpenAlex
- W2028573045
- Cited by
- 209
- References
- 0
- FWCI
- 10.38
- Type
- journal article
- Language
- en
- Open access
- closed
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Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
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Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
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.
