English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Tools annual

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools monthly

Global: Zendy Plus monthly

Presents the access of premium content as premium feature

Premium Content

Global: Zendy Plus annual

Global: Zendy Free Plan

Gender discrimination in hiring is a pertinent and persistent bias insociety, and a common motivating example for exploring bias in NLP. However,the manifestation of gendered language in application materials has receivedlimited attention. This paper investigates the framing of skills and backgroundin CVs of self-identified men and women. We introduce a data set of 1.8Kauthentic, English-language, CVs from the US, covering 16 occupations, allowingus to partially control for the confound occupation-specific gender base rates.We find that (1) women use more verbs evoking impressions of low power; and (2)classifiers capture gender signal even after data balancing and removal ofpronouns and named entities, and this holds for both transformer-based andlinear classifiers.

Professional Presentation and Projected Power: A Case Study of Implicit Gender Information in English CVs