Universität zu Köln

Agnetis, Alessandro ORCID: 0000-0001-5803-0438, Benini, Mario ORCID: 0000-0001-7019-2886, Detti, Paolo, Hermans, Ben ORCID: 0000-0002-7907-6985, Pranzo, Marco and Schewior, Kevin ORCID: 0000-0003-2236-0210 (2025). Replication and sequencing of unreliable jobs on m parallel machines: New results. Computers & Operations Research, 183. pp. 1-14. Elsevier. ISSN 0305-0548

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Abstract

[Artikel-Nr.: 107085] Experimental studies on (implicit) gender biases often deal with the problem of subtly revealing gender, yet without making the study's focus too salient. One prominent solution is to indicate gender through first names. While easy to apply, this method may be prone to confounds: first names may carry various perceptions beyond gender, such as age, socio-economic status, or other traits. We examine the relevance of potential confounds in a comprehensive survey experiment with 4,000 participants of a wide age range (between 18 and 65 years), each rating one of 20 common and timeless first names (10 male and 10 female) on 7 demographic, 9 labor-market relevant and 13 further personal characteristics. We demonstrate that first names actually evoke perceptions beyond gender and show that certain names are consistently and significantly perceived as more prosocial, assertive, or positive / negative than other common and timeless first names of the same gender. Our results send a clear message to experimental studies using first names to convey gender, namely to take into account the perceptions the selected names evoke beyond gender in order to avoid being misled by confounding perceptions. Our data set can serve as a valuable resource for future experimental studies, allowing researchers to choose names that evoke – among a wide age range of participants – similar or diverse associations across different characteristics.

Item Type:	Article
Creators:	Creators Email ORCID ORCID Put Code Agnetis, Alessandro UNSPECIFIED https://orcid.org/0000-0001-5803-0438 UNSPECIFIED Benini, Mario UNSPECIFIED https://orcid.org/0000-0001-7019-2886 UNSPECIFIED Detti, Paolo UNSPECIFIED UNSPECIFIED UNSPECIFIED Hermans, Ben UNSPECIFIED https://orcid.org/0000-0002-7907-6985 UNSPECIFIED Pranzo, Marco UNSPECIFIED UNSPECIFIED UNSPECIFIED Schewior, Kevin UNSPECIFIED https://orcid.org/0000-0003-2236-0210 UNSPECIFIED
URN:	urn:nbn:de:hbz:38-803319
Identification Number:	10.1016/j.cor.2025.107085
Journal or Publication Title:	Computers & Operations Research
Volume:	183
Page Range:	pp. 1-14
Number of Pages:	14
Date:	November 2025
Publisher:	Elsevier
ISSN:	0305-0548
Language:	English
Faculty:	Faculty of Mathematics and Natural Sciences
Divisions:	Faculty of Mathematics and Natural Sciences > Department of Mathematics and Computer Science > Institute of Computer Science
Subjects:	Data processing Computer science Mathematics
Uncontrolled Keywords:	Keywords Language Scheduling ; Approximation algorithms Unreliable jobs ; Unrecoverable breakdowns ; Job replication ; Submodular optimization English
['eprint_fieldname_oa_funders' not defined]:	Publikationsfonds UzK
Refereed:	Yes
URI:	http://kups.ub.uni-koeln.de/id/eprint/80331