Posted: 20 Jun. 2019 05 min. read

Descriptive norms and gender diversity on hiring outcomes

Gender Diversity

Descriptive norms can serve as a potential policy tool to guide individuals to comply with a social norm (Thaler & Sustein, 2008). The literature on descriptive norms is based on the theory that individual decision makers conform to social norms and descriptive norms lead to norm-consistent behaviour (Cialdini et al., 2006). However, research has indicated that descriptive norms are not always effective in guiding behaviour across all domains, and may even lead to increases in undesirable behaviour. This is often due to when the norm information threatens the representation and status of the members of specific groups, leading them to take actions to improve their group’s social identity.

Professors Maliheh Paryavi, Iris Bohnet (Harvard University, United States), and Alexandra van Geen (Erasmus University Rotterdam, Netherlands) explored whether descriptive norms positively influence the hiring of women. In particular, the researchers examined whether social information influenced the gender composition of a group of people (“employees”) selected by others (“employers”) in a work context. Specifically, “employers” were asked to select the number female and male “employees” they next wanted to select for hire, after they were advised of the number of women hired so far during a recruitment process. The researchers then evaluated whether the employers were more likely to hire more of one gender when informed that others have done so as well – or whether in fact it caused backlash. 


The researchers aimed to explore the effect of descriptive gender norm information on hiring decisions that involve male and female employees using a series of laboratory experiments.


The experimental design consisted of two stages.

Stage 1 (Control group): Data was collected through a series of laboratory experiments to understand typical hiring behaviour – and thus determine a baseline. 

  • Over four sessions, 52 employers decided which five employees to recruit for both math and verbal tasks, with evidence of previous performance on similar tasks.
  • The sample of employees consisted of 10 male and 10 female candidates, where the top four employees (2 male, 2 female) had the same performance scores, and the two next best candidates (1 male, 1 female) did not have the exact same performance scores but had the same average.

Stage 2 (Experimental group): The purpose of this stage was to study the impact of gender norms on the hiring decisions, as established in Stage 1, on another set of employers. 

  • Over six sessions, 192 employers, students at the Harvard Decision Science Laboratory in Cambridge, MA, decided which five employees to recruit for math and verbal tasks, with the same sample of 10 male and 10 female “employees” as Stage 1.
  • Two of the six sessions were control sessions, whereby the experiment ran as it did in Stage 1.
  • In the remaining four sessions, the researchers identified the gender of the successful applicant and framed that information in terms of a “gain”. In the male framed condition, employers were informed “in a previous experimental session exactly like yours, X% of people chose more men than women”. In the female frame condition, employers were informed “in a previous experimental session exactly like yours, Y% of people chose more women than men”.
  • The researchers then measured the number of men and women selected in each of these conditions, compared to the baseline determined in Stage 1.  

Findings and implications

When reviewing the control group findings, where no information on previous employer choices was provided, neither male nor female employers showed significant stereotypical hiring tendencies (i.e., hiring more men for math’s based tasks or women for verbal based tasks).  

The researchers then reviewed the experimental framing conditions and found that:

  • No influence on women hirers: Female employers were not influenced by descriptive norm information. When norm information favoured women, the likelihood that female employers selected majority women employees was 50% in the math task and 47% in the verbal task. When the norm conditions favoured men, female employers chose women employees 55% of the time in the math task and 47% in the verbal task. 
  • No influence on male hirers when conditions favoured men: Male employers were not affected by norms that favoured men. Exactly 50% of the male employers chose female majority groups in both the math and the verbal task when they received the norm that favoured men.
  • Negative influence on male hirers when conditions favoured women: When employers learned that previous employers in Stage 1 had chosen mostly women, 35.7% of Stage 2 male employers chose female majority groups, significantly below an equal split.
  • No information assisted female recruits: A regression analysis showed that the average male employer was 20% more likely to select a group of mostly women when no norm information was provided, than when the norm favoured women.


Notably, there was no policy or quota system in place that might have influenced the research participants’ choices and therefore the study outcomes. This was a study of subtle influence. Positively, the “employers” in the control sessions employers did not start with gender-biased preferences, and hence there was little to ‘correct’. The findings regarding the influence of descriptive norms were intriguing, particularly the response from women (namely that they were uninfluenced by norm information or its frame) and the contrasting response from men (namely a pronounced reaction to norms that favoured women, while they were not affected by norm information that favoured men). This suggests both that normative cues require tailoring to their audiences, rather than a one-size-fits-all approach, and that perceived self-interest/identity is a relevant factor. 

Meet our author

Parul Gupta

Parul Gupta

Senior Tax Analyst

Parul is a senior analyst specialising in tax in the financial services industry in Melbourne. She has experience providing taxation compliance and advisory services to the wealth and asset management sector, specialising in funds management (domestic and offshore), superannuation and Shariah compliant arrangements. Parul holds a Bachelor of Law and Bachelor of Business and is admitted to practice as an Australian lawyer.