Perceived warmth and competence are found to influence how race, gender, and age affect callback decisions in hiring processes, suggesting that biases in hiring may be rooted in social perceptions. According to a recent meta-analysis published in the open-access journal PLOS ONE on July 10, 2024, by Carina Hausladen from the California Institute of Technology and ETH Zürich, Marcos Gallo from the California Institute of Technology, and their colleagues.
Perceived warmth and competence predict the influence of race, gender, and age on callback decisions, suggesting social perceptions might underlie such hiring bias. The meta-analysis of North American correspondence studies is published July 10, 2024, in the open-access journal PLOS ONE by Carina Hausladen from the California Institute of Technology and ETH Zürich, Marcos Gallo from the California Institute of Technology, and colleagues.
Individuals from marginalized groups often face unfair treatment in the job market. To investigate bias in hiring, researchers use experimental studies called correspondence studies. In these studies, a set of artificial resumes, identical except for a single detail indicating identity, are presented to employers. By analyzing callback decisions, researchers can uncover discriminatory patterns.
Hausladen and her team explored the relationship between social perceptions of candidates and callback decisions. They examined whether different social perceptions linked to stereotypes of specific identities could explain the differences observed in callback rates. The researchers used the dimensions of social perception, warmth (good intentions), and competence (ability to execute intentions) to assess how people categorize each other.
The team analyzed callback rates from 21 correspondence studies conducted in the US and Canada. These studies varied either the applicants’ names or attributes to indicate identity (e.g., “Sarah Davis” potentially signaling a white female, or mentioning volunteering at a church to indicate religious affiliation). Participants, representing North American hiring managers demographically, evaluated the applicants based on perceived warmth and competence.
The analysis revealed that in studies where names indicated race, gender, and age, ratings of warmth and competence predicted differences in callback rates between identities. Applicants with lower callback rates were often perceived as less warm and competent, and vice versa. This suggests that identity cues can trigger specific warmth and competence perceptions based on stereotypes, influencing callback decisions. However, for studies varying attributes to signal other categories like sexuality and disability, the effect of social perception on callbacks was inconsistent.
Social perceptions can differ across cultures, and some correspondence studies had relatively small sample sizes, limiting the generalizability of the findings. The researchers urge future studies to include intersectional research to broaden and diversify the attributes examined.
The researchers intend to use the connection between perceived warmth, competence, and callback rates to gain deeper insights into hiring discrimination and potentially address biases in the increasingly prevalent Large Language Models used for resume evaluations.
