--- title: "Who cites Disagreeable, Slovenly, Honest — 2 citing papers" description: "2 papers of the Elamur Research library cite «Disagreeable, Slovenly, Honest and Un-named Women? Investigating Gender Bias in English…" canonical: "https://research.elamur.ai/free/en/papers/zhu-2024-disagreeable-slovenly-honest-un-named/cited-by/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/papers/zhu-2024-disagreeable-slovenly-honest-un-named/cited-by/) [home](https://md.research.elamur.ai/free/en/) / [papers](https://md.research.elamur.ai/free/en/papers/) / [Disagreeable, Slovenly, Honest and Un-named…](https://md.research.elamur.ai/free/en/papers/zhu-2024-disagreeable-slovenly-honest-un-named/) / cited by # Who cites «Disagreeable, Slovenly, Honest and Un-named Women? Investigating Gender Bias in English Educational Resources by Extending Existing Gender Bias Taxonomies» 2 papers of our library cite it (of the 149,439 whose bibliographies we read) · 2 with a page here, the most cited first · [← back to «Disagreeable, Slovenly, Honest and Un-named Women? Investigating Gender Bias in English Educational Resources by Extending Existing Gender Bias Taxonomies»](https://md.research.elamur.ai/free/en/papers/zhu-2024-disagreeable-slovenly-honest-un-named/) 1. **[Remedying Gender Bias in Open English Wordnet](https://md.research.elamur.ai/free/en/papers/mccrae-2025-remedying-gender-bias-open-english/) [Global Wordnet Conference](https://md.research.elamur.ai/free/en/venues/gwc/)**John P. McCrae, Haotian Zhu, Fei Xia, et al.*2025 · 1 citation* 2. **[CANVAS: A Multimodal Dataset of Chinese Textbook Images for Bias and Representation Analysis](https://md.research.elamur.ai/free/en/papers/zhu-2026-canvas-multimodal-dataset-chinese-textbook/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Haotian Zhu, Kefan Yu, Min Li*2026* - [← back to](https://md.research.elamur.ai/free/en/papers/zhu-2024-disagreeable-slovenly-honest-un-named/) — Disagreeable, Slovenly, Honest and Un-named Women? Investigating Gender Bias in English Educational Resources by Extending Existing Gender Bias Taxonomies