arXiv Open Access 2024

Dynamics of Gender Bias within Computer Science

Thomas J. Misa
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Abstrak

A new dataset (N = 7,456) analyzes women's research authorship in the Association for Computing Machinery's founding 13 Special Interest Groups or SIGs, a proxy for computer science. ACM SIGs expanded during 1970-2000; each experienced increasing women's authorship. But diversity abounds. Several SIGs had fewer than 10% women authors while SIGUCCS (university computing centers) exceeded 40%. Three SIGs experienced accelerating growth in women's authorship; most, including a composite ACM, had decelerating growth. This research may encourage reform efforts, often focusing on general education or workforce factors (across the entity of "computer science"), to examine under-studied dynamics within computer science that shaped changes in women's participation.

Topik & Kata Kunci

Penulis (1)

T

Thomas J. Misa

Format Sitasi

Misa, T.J. (2024). Dynamics of Gender Bias within Computer Science. https://arxiv.org/abs/2407.08102

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Tahun Terbit
2024
Bahasa
en
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arXiv
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Open Access ✓