Cookies?
Library Header Image
LSE Research Online LSE Library Services

How clicks on a job platform can reveal gender, ethnic, and racial bias

Hangartner, Dominik, Kopp, Daniel and Siegenthaler, Michael (2021) How clicks on a job platform can reveal gender, ethnic, and racial bias. LSE Business Review (01 Apr 2021). Blog Entry.

[img] Text (businessreview-2021-04-01-how-clicks-on-a-job-platform-can-reveal) - Published Version
Download (446kB)

Abstract

Education and skills should be the key determinants of whether a candidate gets a job or not, but in reality, gender, origin or race/ethnicity end up influencing hiring decisions. By leveraging big data from recruitment platforms and machine learning to study hiring discrimination, Dominik Hangartner, Daniel Kopp, and Michael Siegenthaler show that discrimination against immigrants depends, among other things, on their origin and time of day; and that both men and women face discrimination.

Item Type: Online resource (Blog Entry)
Official URL: https://blogs.lse.ac.uk/businessreview/
Additional Information: © 2021 The Authors
Divisions: Government
Subjects: H Social Sciences > HD Industries. Land use. Labor
H Social Sciences > HD Industries. Land use. Labor > HD28 Management. Industrial Management
Date Deposited: 27 May 2021 10:33
Last Modified: 01 Aug 2021 23:04
URI: http://eprints.lse.ac.uk/id/eprint/110574

Actions (login required)

View Item View Item

Downloads

Downloads per month over past year

View more statistics