PLoS ONE 16(12):Įditor: Aurora García-Gallego, Universitat Jaume I, SPAIN Ĭitation: Martínez N, Vinas A, Matute H (2021) Examining potential gender bias in automated-job alerts in the Spanish market. The data and materials for this research are available at the Open Science Framework. Some limitations and implications of the study are discussed. However, we found significant differences between the female-dominated and the male-dominated sectors in all the mentioned variables. No significant differences were observed in the automated-job alerts received by female and male candidates as a function of occupation category, salary, and the number of long-term contracts included in the alerts. male-dominated) and two different levels of age (24 vs.
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Based on the correspondence testing procedure, we designed eight matched resumes in which we manipulated the gender of the candidate for two different professional sectors (female-dominated vs. The present research aimed to explore a possible gender bias in automated-job alerts generated in InfoJobs, a popular job platform in Spain.
However, previous research has shown that algorithms can exhibit and even amplify gender bias. Nowadays, algorithms and job platforms are used for personnel selection processes because of their supposed neutrality, efficiency, and costs savings. Numerous field experiments based on the correspondence testing procedure have documented that gender bias influences personnel selection processes.
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