The paper describes the results of an experimental study carried out by sending bogus CVs in response to online posts. To each post related to a job vacation in a Veneto industry a number of five CVs was created and sent. The CVs were created so to experimentally evaluate the likelihood of discrimination against certain categories of candidates. The variability of call back rates of the addressed industries was analysed to elicit possible relationships between recruiters’ taste and gender, nationality, academic curriculum and other social characteristics of applicants. Contrary to expectations, women obtained more call backs than male counterparts and graduates in a social or humanistic discipline were called back more than graduates in a scientific or technical one. Even the possession of a car was negatively evaluated by recruiters. As expected, instead, foreign-born candidates obtained far less call backs than Italian ones. A multivariate analysis drew us to the conclusion that the largest part of online posts was destined to candidates who belonged to intermediate categories, that is, to candidates being the best once the bottom and the top candidates were skimmed. The worst candidates were excluded for intuitive reasons, while the excellent ones – we conjecture – were left aside because recruiters guessed they would demand more than companies were available to give. These outcomes could help graduates in their duty of preparing an ad hoc CV.
University of Padua, Italy - ORCID: 0000-0001-8657-8361
Titolo del capitolo
The top candidate is an intermediate one: An analysis of online posts of Veneto industries
Autori
Luigi Fabbris
Lingua
English
DOI
10.36253/978-88-5518-461-8.05
Opera sottoposta a peer review
Anno di pubblicazione
2021
Copyright
© 2021 Author(s)
Licenza d'uso
Licenza dei metadati
Titolo del libro
ASA 2021 Statistics and Information Systems for Policy Evaluation
Sottotitolo del libro
BOOK OF SHORT PAPERS of the on-site conference
Curatori
Bruno Bertaccini, Luigi Fabbris, Alessandra Petrucci
Opera sottoposta a peer review
Anno di pubblicazione
2021
Copyright
© 2021 Author(s)
Licenza d'uso
Licenza dei metadati
Editore
Firenze University Press
DOI
10.36253/978-88-5518-461-8
eISBN (pdf)
978-88-5518-461-8
eISBN (xml)
978-88-5518-462-5
Collana
Proceedings e report
ISSN della collana
2704-601X
e-ISSN della collana
2704-5846