Age-discrimination in job-vacancy texts: An automated content analysis into forbidden age-based discriminatory language use in job-vacancy texts. Report commisioned by The Netherlands Institute for Human Rights

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Abstract

This report describes a study into age discrimination in job-vacancy texts, which we conducted for "The Netherlands Institute for Human Rights". Using automated content analysis techniques we analysed almost all Dutch-language vacancy texts published on the internet in 2017. This involves more than 1.8 million unique job-vacancy texts. The developed algorithm detects forbidden age-based discriminatory formulations that either directly or indirectly express a preference for certain age groups in candidates. Based on the results and our reliability analysis, we conservatively estimate the number of actual cases of direct age discrimination to be at least 8,000 (0.44% of total vacancy texts) and at least 61,000 (3.33% of total) cases of indirect discrimination. Most detected forbidden formulations call for young candidates, by which older candidates are either directly or indirectly excluded.
Translated title of the contributionAge-discrimination in job-vacancy texts: An automated content analysis into forbidden age-based discriminatory language use in job-vacancy texts.: Report commisioned by The Netherlands Institute for Human Rights
Original languageDutch
Commissioning bodyCollege voor de Rechten van de Mens
Number of pages27
Publication statusPublished - 15 Mar 2018

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job vacancy
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title = "Leeftijdsdiscriminatie in vacatureteksten: Een geautomatiseerde inhoudsanalyse naar verboden leeftijd-gerelateerd taalgebruik in vacatureteksten: Rapport in opdracht van het College voor de Rechten van de Mens.",
abstract = "This report describes a study into age discrimination in job-vacancy texts, which we conducted for {"}The Netherlands Institute for Human Rights{"}. Using automated content analysis techniques we analysed almost all Dutch-language vacancy texts published on the internet in 2017. This involves more than 1.8 million unique job-vacancy texts. The developed algorithm detects forbidden age-based discriminatory formulations that either directly or indirectly express a preference for certain age groups in candidates. Based on the results and our reliability analysis, we conservatively estimate the number of actual cases of direct age discrimination to be at least 8,000 (0.44{\%} of total vacancy texts) and at least 61,000 (3.33{\%} of total) cases of indirect discrimination. Most detected forbidden formulations call for young candidates, by which older candidates are either directly or indirectly excluded.",
author = "A.S. Fokkens and C.J. Beukeboom and E. Maks",
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AU - Maks, E.

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AB - This report describes a study into age discrimination in job-vacancy texts, which we conducted for "The Netherlands Institute for Human Rights". Using automated content analysis techniques we analysed almost all Dutch-language vacancy texts published on the internet in 2017. This involves more than 1.8 million unique job-vacancy texts. The developed algorithm detects forbidden age-based discriminatory formulations that either directly or indirectly express a preference for certain age groups in candidates. Based on the results and our reliability analysis, we conservatively estimate the number of actual cases of direct age discrimination to be at least 8,000 (0.44% of total vacancy texts) and at least 61,000 (3.33% of total) cases of indirect discrimination. Most detected forbidden formulations call for young candidates, by which older candidates are either directly or indirectly excluded.

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