The DOI matches its Crossref record; 58 of the 58 references it cites were found in a registry or an index.
Do you identify as a gamer? Gender, race, sexuality, and gamer identity
Abstract
The demand for minority representation in video games often focuses on proving that members of marginalized groups are gamers. In turn, it is asserted that the gaming industry should focus on appealing to these players via targeted content. Being targeted as a gamer, however, does not a gamer make. Identity as a gamer intersects with other identities like gender, race, and sexuality. Negative connotations about gaming lead people to not identify as gamers, and even to not play video games. This article concludes, based on interview data, that those invested in diversity in video games must focus their attention on the construction of the medium, and not the construction of the audience as such. This shift in academic attention is necessary to develop arguments for representation in games that do not rely on marking groups as specific kinds of gaming markets via identifiers like gender, race, and sexuality.
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Cites
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Cited by
Snodgrass, J. G., Bagwell, A., Patry, J. M., Dengah, H. J. F., Smarr-Foster, C., Van Oostenburg, M., & Lacy, M. G. (2018) · Computers in Human Behavior · doi:10.1016/j.chb.2017.09.020 · Cited by 82
The #GamerGate Files: Misogyny in the Media
Kidd, D., & Turner, A. J. (2016) · Advances in Human and Social Aspects of Technology · doi:10.4018/978-1-5225-0212-8.ch008 · Cited by 21
Metadata
- Authors
- Shaw, A.
- Venue
- New Media & Society
- Publisher
- SAGE Publications
- Published
- 2011-06-16
- Volume
- 14
- Issue
- 1
- Pages
- 28-44
- ISSN
- 1461-4448 (ISSN-L)
- 1461-7315
- OpenAlex
- W2160279118
- Cited by
- 444
- References
- 58
- FWCI
- 18.22
- Type
- journal article
- Language
- en
- Open access
- closed
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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.