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Citational politics: Quantifying the influence of gender on citation in Digital Scholarship in the Humanities
Abstract
Using citation analysis, we consider the role of gender in citation practices in conference special issues of Digital Scholarship in the Humanities. Our examination of citations in Digital Humanities conference special issues from 2006 to 2015 demonstrates gender bias in citational practices. This bias is consistent with broader trends in citational politics across the academy more broadly but is a threat to equity and justice within the scholarly community. We further offer proposals for improving citational practices to resist gender bias. Quantifying the impact of gender on citations, we argue, is one approach to understanding gender inequalities within digital humanities communities and to generating solutions to promote the broadest representation of digital humanities scholarship in scholarly communications.
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“Information behavior research-encompassing how people seek, use, share, and assess information needs-has documented scholarship across countries with varying economic development levels, providing the geographic breadth necessary for our analysis (Earhart et al., 2021).”
From Geographic Variation in LLM DOI Fabrication: Cross-Country Analysis of Citation Accuracy Across Four Large Language Models (2025) · cites this paper as Earhart et al., 2021
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Cited by
Kim, E., Kipchumba, F., & Min, S. (2025) · Publications · doi:10.3390/publications13040049 · Cited by 7
Metadata
- Authors
- Earhart, A. E., Risam, R., & Bruno, M.
- Affiliations
- Department of English, Texas A&M University, USA
- Departments of Secondary and Higher Education and English, Salem State University, USA
- Department of English, Salem State University, USA
- ORCID
- Risam, Roopika
- Venue
- Digital Scholarship in the Humanities
- Publisher
- Oxford University Press (OUP)
- Published
- 2020-08-03
- Volume
- 36
- Issue
- 3
- Pages
- 581-594
- ISSN
- 2055-7671
- 2055-768X
- Cited by
- 11
- References
- 1
- Language
- en
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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.