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"Personnel Selection"
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Science faculty’s subtle gender biases favor male students
Despite efforts to recruit and retain more women, a stark gender disparity persists within academic science. Abundant research has demonstrated gender bias in many demographic groups, but has yet to experimentally investigate whether science faculty exhibit a bias against female students that could contribute to the gender disparity in academic science. In a randomized double-blind study (n = 127), science faculty from research-intensive universities rated the application materials of a student—who was randomly assigned either a male or female name—for a laboratory manager position. Faculty participants rated the male applicant as significantly more competent and hireable than the (identical) female applicant. These participants also selected a higher starting salary and offered more career mentoring to the male applicant. The gender of the faculty participants did not affect responses, such that female and male faculty were equally likely to exhibit bias against the female student. Mediation analyses indicated that the female student was less likely to be hired because she was viewed as less competent. We also assessed faculty participants’ preexisting subtle bias against women using a standard instrument and found that preexisting subtle bias against women played a moderating role, such that subtle bias against women was associated with less support for the female student, but was unrelated to reactions to the male student. These results suggest that interventions addressing faculty gender bias might advance the goal of increasing the participation of women in science.
Journal Article
Monitoring hiring discrimination through online recruitment platforms
Women (compared to men) and individuals from minority ethnic groups (compared to the majority group) face unfavourable labour market outcomes in many economies
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,
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, but the extent to which discrimination is responsible for these effects, and the channels through which they occur, remain unclear
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,
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. Although correspondence tests
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—in which researchers send fictitious CVs that are identical except for the randomized minority trait to be tested (for example, names that are deemed to sound ‘Black’ versus those deemed to sound ‘white’)—are an increasingly popular method to quantify discrimination in hiring practices
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,
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, they can usually consider only a few applicant characteristics in select occupations at a particular point in time. To overcome these limitations, here we develop an approach to investigate hiring discrimination that combines tracking of the search behaviour of recruiters on employment websites and supervised machine learning to control for all relevant jobseeker characteristics that are visible to recruiters. We apply this methodology to the online recruitment platform of the Swiss public employment service and find that rates of contact by recruiters are 4–19% lower for individuals from immigrant and minority ethnic groups, depending on their country of origin, than for citizens from the majority group. Women experience a penalty of 7% in professions that are dominated by men, and the opposite pattern emerges for men in professions that are dominated by women. We find no evidence that recruiters spend less time evaluating the profiles of individuals from minority ethnic groups. Our methodology provides a widely applicable, non-intrusive and cost-efficient tool that researchers and policy-makers can use to continuously monitor hiring discrimination, to identify some of the drivers of discrimination and to inform approaches to counter it.
An analysis of the search behaviour of recruiters on a Swiss online recruitment platform shows that jobseekers from minority ethnic groups are less likely to be contacted by recruiters, and also provides evidence of gender-based discrimination.
Journal Article
To diversify the scientific workforce, postdoc recruitment needs a rethink
Biased hiring practices are limiting efforts to attract and retain researchers of colour.
Biased hiring practices are limiting efforts to attract and retain researchers of colour.
Credit: Kaat Hebbelinck
Devang Mehta holding a plant and bathed in a pink light emanating from a growing chamber
Journal Article
A prescription for nursing: five measures to remedy the ills of the profession
Anne Marie Rafferty and Aisha Holloway discuss five ways to improve working conditions for the nursing profession, which will also have benefits for healthcare professionals more generally
Journal Article
A projection-based TODIM method under multi-valued neutrosophic environments and its application in personnel selection
The personnel selection is a vital activity for companies, and multi-valued neutrosophic sets (MVNSs) can denote the fuzziness and hesitancy in the processes of the personnel selection. The extant fuzzy TODIM (an acronym in Portuguese of interactive and multi-criteria decision-making) methods take advantage of distance to denote the difference between two fuzzy sets (FSs). Nevertheless, the distance measurement, which ignores the included angle between two FSs, cannot comprehensively reflect the difference between two FSs. To cover this defect, a projection-based TODIM method with MVNSs for personnel selection is established to consider the risk preference of decision-makers and overcome the defect of the extant fuzzy TODIM methods. The proposed TODIM method makes use of an improved comparison method which overcomes the deficiency of extant comparison method. Furthermore, a projection-based difference measurement is defined and utilized in the projection-based TODIM method. We conduct a numerical example of the personnel selection to explain the application of the projection-based TODIM method and discuss the influence of the parameter. Finally, the proposed method is compared with several extant methods to verify its feasibility.
Journal Article