Beyond the gender bias: Identifying gendered language in job advertisements and predicting organisational diversity outcomes using embedding methods, POS tagging and predictive modelling

Additional Metadata
Keywords	gender inequality; diversity; gendered wording; job advertisements; NLP
Thesis Advisor	Malek, S.L.
Persistent URL	hdl.handle.net/2105/59117
Series	Business Economics
Organisation	Erasmus School of Economics
Citation APA APA Style APA-ALL Style AAA Style Cell Style Chicago Style Harvard Style IEEE Style MLA Style Nature Style Vancouver Style American-Institute-of-Physics Style Council-of-Science-Editors Style BibTex Format Endnote Format RIS Format CSL Format DOIs only Format	Giesen, K.A. (2021). Beyond the gender bias: Identifying gendered language in job advertisements and predicting organisational diversity outcomes using embedding methods, POS tagging and predictive modelling. In Business Economics.http://hdl.handle.net/2105/59117

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