{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,26]],"date-time":"2026-03-26T14:16:22Z","timestamp":1774534582820,"version":"3.50.1"},"reference-count":14,"publisher":"Association for Computing Machinery (ACM)","issue":"CSCW","license":[{"start":{"date-parts":[[2017,12,6]],"date-time":"2017-12-06T00:00:00Z","timestamp":1512518400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"funder":[{"DOI":"10.13039\/100000001","name":"National Science Foundation","doi-asserted-by":"publisher","award":["CNS-1527939"],"award-info":[{"award-number":["CNS-1527939"]}],"id":[{"id":"10.13039\/100000001","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000001","name":"National Science Foundation","doi-asserted-by":"publisher","award":["CNS-1705042"],"award-info":[{"award-number":["CNS-1705042"]}],"id":[{"id":"10.13039\/100000001","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":["Proc. ACM Hum.-Comput. Interact."],"published-print":{"date-parts":[[2017,12,6]]},"abstract":"<jats:p>\n            For millions of workers, online job listings provide the first point of contact to potential employers. As a result, job listings and their word choices can significantly affect the makeup of the responding applicant pool. Here, we study the effects of potentially gender-biased terminology in job listings, and their impact on job applicants, using a large historical corpus of 17 million listings on LinkedIn spanning 10 years. We develop algorithms to detect and quantify gender bias, validate them using external tools, and use them to quantify job listing bias over time. We then perform a user survey over two user populations (N\n            <jats:sub>1=469<\/jats:sub>\n            , N\n            <jats:sub>2=273<\/jats:sub>\n            ) to validate our findings and to quantify the end-to-end impact of such bias on applicant decisions. Our findings show gender-bias has decreased significantly over the last 10 years. More surprisingly, we find that impact of gender bias in listings is dwarfed by our respondents' inherent bias towards specific job types.\n          <\/jats:p>","DOI":"10.1145\/3134734","type":"journal-article","created":{"date-parts":[[2017,12,6]],"date-time":"2017-12-06T21:23:15Z","timestamp":1512595395000},"page":"1-19","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":37,"title":["Gender Bias in the Job Market"],"prefix":"10.1145","volume":"1","author":[{"given":"Shiliang","family":"Tang","sequence":"first","affiliation":[{"name":"University of California, Santa Barbara, Santa Barbara, CA, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xinyi","family":"Zhang","sequence":"additional","affiliation":[{"name":"University of California, Santa Barbara, Santa Barbara, CA, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jenna","family":"Cryan","sequence":"additional","affiliation":[{"name":"University of Chicago, Chicago, IL, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Miriam J.","family":"Metzger","sequence":"additional","affiliation":[{"name":"University of California, Santa Barbara, Santa Barbara, CA, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Haitao","family":"Zheng","sequence":"additional","affiliation":[{"name":"University of Chicago, Chicago, IL, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ben Y.","family":"Zhao","sequence":"additional","affiliation":[{"name":"University of Chicago, Chicago, IL, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2017,12,6]]},"reference":[{"key":"e_1_2_1_1_1","volume-title":"Aggarwal and ChengXiang Zhai","author":"Charu","year":"2012","unstructured":"Charu C. Aggarwal and ChengXiang Zhai . 2012 . A survey of text classification algorithms. Mining text data (2012), 163--222. Charu C. Aggarwal and ChengXiang Zhai. 2012. A survey of text classification algorithms. Mining text data (2012), 163--222."},{"key":"e_1_2_1_2_1","doi-asserted-by":"publisher","DOI":"10.1111\/gwao.12053"},{"key":"e_1_2_1_3_1","doi-asserted-by":"publisher","DOI":"10.1023\/B:SERS.0000015551.78544.35"},{"key":"e_1_2_1_4_1","doi-asserted-by":"publisher","DOI":"10.1037\/h0036215"},{"key":"e_1_2_1_5_1","doi-asserted-by":"publisher","DOI":"10.1111\/j.1559-1816.1973.tb01290.x"},{"key":"e_1_2_1_6_1","doi-asserted-by":"publisher","DOI":"10.1257\/0002828042002561"},{"key":"e_1_2_1_7_1","volume-title":"Kahn","author":"Blau Francine D.","year":"2016","unstructured":"Francine D. Blau and Lawrence M . Kahn . 2016 . The gender wage gap: Extent, trends, and explanations. Technical Report. National Bureau of Economic Research . Francine D. Blau and Lawrence M. Kahn. 2016. The gender wage gap: Extent, trends, and explanations. Technical Report. National Bureau of Economic Research."},{"key":"e_1_2_1_8_1","volume-title":"Kalai","author":"Bolukbasi Tolga","year":"2016","unstructured":"Tolga Bolukbasi , Kai-Wei Chang , James Y. Zou , Venkatesh Saligrama , and Adam T . Kalai . 2016 . Man is to computer programmer as woman is to homemaker? Debiasing word embeddings Advances in Neural Information Processing Systems . 4349--4357. Tolga Bolukbasi, Kai-Wei Chang, James Y. Zou, Venkatesh Saligrama, and Adam T. Kalai. 2016. Man is to computer programmer as woman is to homemaker? Debiasing word embeddings Advances in Neural Information Processing Systems. 4349--4357."},{"key":"e_1_2_1_9_1","unstructured":"Anna Brown and Eileen Patten. 2017. The narrowing but persistent gender gap in pay. http:\/\/www.pewresearch.org\/fact-tank\/2017\/04\/03\/gender-pay-gap-facts\/. (2017).  Anna Brown and Eileen Patten. 2017. The narrowing but persistent gender gap in pay. http:\/\/www.pewresearch.org\/fact-tank\/2017\/04\/03\/gender-pay-gap-facts\/. (2017)."},{"key":"e_1_2_1_10_1","doi-asserted-by":"publisher","DOI":"10.1177\/1529100614541236"},{"key":"e_1_2_1_11_1","doi-asserted-by":"publisher","DOI":"10.1177\/0146167299025004002"},{"key":"e_1_2_1_12_1","volume-title":"Women and science careers: leaky pipeline or gender filter? Gender and education","author":"Jacob Clark","year":"2005","unstructured":"Jacob Clark Blickenstaff*. 2005. Women and science careers: leaky pipeline or gender filter? Gender and education , Vol. 17 , 4 ( 2005 ), 369--386. Jacob Clark Blickenstaff*. 2005. Women and science careers: leaky pipeline or gender filter? Gender and education, Vol. 17, 4 (2005), 369--386."},{"key":"e_1_2_1_13_1","doi-asserted-by":"publisher","DOI":"10.1089\/jwh.2007.0582"},{"key":"e_1_2_1_14_1","volume-title":"Twenge","author":"Donnelly Kristin","year":"2016","unstructured":"Kristin Donnelly and Jean M . Twenge . 2016 . Masculine and feminine traits on the Bem Sex-Role inventory, 1993--2012: a cross-temporal meta-analysis. Sex Roles ( 2016), 1--10. Kristin Donnelly and Jean M. Twenge. 2016. Masculine and feminine traits on the Bem Sex-Role inventory, 1993--2012: a cross-temporal meta-analysis. Sex Roles (2016), 1--10."}],"container-title":["Proceedings of the ACM on Human-Computer Interaction"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3134734","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3134734","content-type":"application\/pdf","content-version":"vor","intended-application":"syndication"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3134734","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,18]],"date-time":"2025-06-18T02:11:24Z","timestamp":1750212684000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3134734"}},"subtitle":["A Longitudinal Analysis"],"short-title":[],"issued":{"date-parts":[[2017,12,6]]},"references-count":14,"journal-issue":{"issue":"CSCW","published-print":{"date-parts":[[2017,12,6]]}},"alternative-id":["10.1145\/3134734"],"URL":"https:\/\/doi.org\/10.1145\/3134734","relation":{},"ISSN":["2573-0142"],"issn-type":[{"value":"2573-0142","type":"electronic"}],"subject":[],"published":{"date-parts":[[2017,12,6]]},"assertion":[{"value":"2017-12-06","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}