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- Publisher Website: 10.1098/rsif.2024.0784
- Scopus: eid_2-s2.0-105007499097
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Article: Gender differences in resume language and gender gaps in salary expectations
| Title | Gender differences in resume language and gender gaps in salary expectations |
|---|---|
| Authors | |
| Keywords | computational social science gender gap neural network model resume written language |
| Issue Date | 4-Jun-2025 |
| Publisher | The Royal Society |
| Citation | Journal of the Royal Society Interface, 2025, v. 22, n. 227 How to Cite? |
| Abstract | How men and women present themselves in their resumes may affect their opportunity in job seeking. To investigate gender differences in resume writing and how they are associated with gender gaps in the labour market, we analysed 6.9 million resumes of Chinese job applicants in this study. Results reveal substantial gender resume differences, where women and men show distinct patterns in both simple language features and high-level semantic structures in the word embedding space of resumes. In particular, women tend to use shorter resumes, longer sentences and a more diverse set of unique words. Neural network models trained on resumes can predict gender with 80% accuracy, and the accuracy decreases with education levels and text standardization requirements. Moreover, while better language skills are associated with higher salary expectations, this positive relationship is magnified for men but weakened for women in women-dominated occupations. This study presents a new venue for the understanding of gender differences and provides empirical findings on how men and women are different in self-portraying and job seeking. |
| Persistent Identifier | http://hdl.handle.net/10722/357649 |
| ISSN | 2023 Impact Factor: 3.7 2023 SCImago Journal Rankings: 1.101 |
| ISI Accession Number ID |
| DC Field | Value | Language |
|---|---|---|
| dc.contributor.author | Qu, Qian | - |
| dc.contributor.author | Liu, Quan Hui | - |
| dc.contributor.author | Gao, Jian | - |
| dc.contributor.author | Huang, Shudong | - |
| dc.contributor.author | Feng, Wentao | - |
| dc.contributor.author | Yue, Zhongtao | - |
| dc.contributor.author | Lu, Xin | - |
| dc.contributor.author | Zhou, Tao | - |
| dc.contributor.author | Lv, Jiancheng | - |
| dc.date.accessioned | 2025-07-22T03:14:04Z | - |
| dc.date.available | 2025-07-22T03:14:04Z | - |
| dc.date.issued | 2025-06-04 | - |
| dc.identifier.citation | Journal of the Royal Society Interface, 2025, v. 22, n. 227 | - |
| dc.identifier.issn | 1742-5689 | - |
| dc.identifier.uri | http://hdl.handle.net/10722/357649 | - |
| dc.description.abstract | <p>How men and women present themselves in their resumes may affect their opportunity in job seeking. To investigate gender differences in resume writing and how they are associated with gender gaps in the labour market, we analysed 6.9 million resumes of Chinese job applicants in this study. Results reveal substantial gender resume differences, where women and men show distinct patterns in both simple language features and high-level semantic structures in the word embedding space of resumes. In particular, women tend to use shorter resumes, longer sentences and a more diverse set of unique words. Neural network models trained on resumes can predict gender with 80% accuracy, and the accuracy decreases with education levels and text standardization requirements. Moreover, while better language skills are associated with higher salary expectations, this positive relationship is magnified for men but weakened for women in women-dominated occupations. This study presents a new venue for the understanding of gender differences and provides empirical findings on how men and women are different in self-portraying and job seeking.</p> | - |
| dc.language | eng | - |
| dc.publisher | The Royal Society | - |
| dc.relation.ispartof | Journal of the Royal Society Interface | - |
| dc.rights | This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License. | - |
| dc.subject | computational social science | - |
| dc.subject | gender gap | - |
| dc.subject | neural network model | - |
| dc.subject | resume | - |
| dc.subject | written language | - |
| dc.title | Gender differences in resume language and gender gaps in salary expectations | - |
| dc.type | Article | - |
| dc.identifier.doi | 10.1098/rsif.2024.0784 | - |
| dc.identifier.scopus | eid_2-s2.0-105007499097 | - |
| dc.identifier.volume | 22 | - |
| dc.identifier.issue | 227 | - |
| dc.identifier.eissn | 1742-5662 | - |
| dc.identifier.isi | WOS:001501540900002 | - |
| dc.identifier.issnl | 1742-5662 | - |
