Banishing occupational stereotypes

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Bombarded with stimuli from every direction, it is not surprising that human observers with finite cognitive resources resort to categorical thinking to simplify incoming information. The problem is, this often manifests itself in a tendency to group individuals on the basis of social categories including race, gender and age. Further, such categories are often imbued with associations and expectations—aka stereotypes—which perceivers use to form impressions and judgments of others.

One little discussed sub-category of stereotypes is ‘occupational stereotypes’—collections of traits or attributes with which individuals associate members of different occupations. In this article we will describe our research into these stereotypes, showing who they effect, how they lead to segregation and their implications for society.

How Stereotypes Lead to Segregation
In 2013, the Ontario Bar Association launched a campaign to combat the public image of lawyers as greedy, aggressive, dishonest and manipulative. The campaign attempted to change the perception of lawyers by stressing their qualities as ‘problem-solvers’ and ‘pillars of their communities’.

Law is not the only profession associated with negative stereotypes. People tend to think of computer scientists and tech developers as possessing immense knowledge and expertise, but lacking in social skills. On the other hand, childcare workers are commonly perceived as being extremely caring—to the point of lacking the assertiveness required to be good leaders.

Understanding the occupational stereotypes that people hold has important implications for vocational behaviour and for other more widespread societal outcomes. At the vocational level, these stereotypes can have important consequences for career choice, such that people are more likely to seek out an occupation with stereotyped attributes that match their own self-perceptions.

Occupational stereotypes can also influence the experience of job-holders themselves by shaping the social expectations that are associated with their positions. Research shows that stereotypes can lead to preconceived notions about individuals and social groups that are not based on reason or reality, and can lead to unjust and differential treatment on the basis of those preconceived notions. As such, occupational stereotypes may have more widespread effects on the distribution of workers across different kinds of jobs—a phenomenon known as ‘occupational segregation’.

While researchers agree that occupational stereotypes exist and have important consequences, there is a lack of consensus regarding the actual dimensions on which individuals judge occupations. A number of studies have found that occupations are stereotyped according to gender, whereas others have focused on status, prestige and likability.

In a recent paper, we proposed that the content of occupational stereotypes can be summarized under two dimensions: warmth and competence. These are the two fundamental dimensions in the Stereotype Content Model developed by Princeton University Professor Susan Fiske and her colleagues. In their well-established framework, ‘warmth’ refers to being perceived as tolerant, good-natured and sincere, reflecting how likable a person is; while ‘competence’ refers to being perceived as confident, competitive and intelligent, and generally reflects how respected an individual or target group is.

In our research we found that people also hold stereotypes of occupations along these two dimensions. For example, the common perception that scientists (e.g. computer scientists, mathematicians, physicists, engineers) are highly intelligent but lack social graces may correspond to perceptions of high competence and low warmth. Similarly, the perception that childcare workers are caring but lack ambition may be represented by perceptions of high warmth and low competence.

Although calls for gender and racial inclusion and integration within the workplace have been voiced for over 40 years, vast discrepancies continue to be the norm, with some scholars referring to the current landscape as one of ‘hyper-segregation’.

Occupational segregation refers to a non-representative distribution of individuals from various demographic categories across certain occupations. Although this phenomenon has been examined most often with regard to women and African Americans, it has also been proven to be a reality for a variety of other social groups, including racial and ethnic minorities, older adults and LGBTQ+ individuals.

To date, researchers have focused on the effects of gendered occupational stereotypes on vocational choice, finding that men and women tend to choose occupations with gender stereotypes that align with their own identity. According to the Lack of Fit Model of gender bias and the Role Incongruity Theory of female leadership, the mismatch between the expectations people hold of certain social groups (e.g., women) and the expected characteristics of certain occupations (e.g., lawyers) leads to bias against women in those occupations. The abundance of research and theory on gendered occupational stereotypes has thus established that individuals do indeed hold stereotypes of occupations based on gender, and that these stereotypes can drive behaviour towards and away from certain occupations.

Research has also examined the consequences of other occupational stereotypes. Some initial work on this question has found evidence of a ‘race-occupation fit’ hypothesis, in which certain racial minorities (e.g., Asians) are perceived to fit certain occupations (e.g., engineering and math) because the demographic stereotype matches the occupational stereotype.

The development of a comprehensive classification of occupational stereotypes based on the aforementioned SCM allowed us to take the first steps toward directly and systematically examining whether the mismatch between occupational stereotypes and any other demographic stereotypes is associated with occupational segregation.

Based on our Model of Stereotype Incongruence, we predicted greater representation of a given social-demographic group within occupations that have congruent stereotypes related to warmth and competence. Compared to men, women are stereotyped as warmer but less competent, so we expected more women to be represented in occupations characterized as ‘highly warm’ and fewer women to be represented in occupations characterized as ‘highly competent’.

Asian individuals are defined in the SCM as being stereotyped as high on competence and mid-level on warmth, so we expected to observe greater representation in occupations classified as highly competent. The stereotype content of the black racial group is more complex and nuanced: Whereas some studies show that subcategories of black people are stereotyped as hostile and aggressive—stereotypes which may be directed primarily toward Black people who are perceived as ‘criminal’ or ‘poor’, modern prejudice scales have categorized blacks as being ambivalently perceived as lazy but disadvantaged (i.e., incompetent but deserving sympathy). Although this past work shows mixed arguments for the stereotype content of blacks, there is a consistent stereotype that blacks tend to be low in competence, overall. As such, we expected higher numbers of black workers to be found in occupations classified in lower competence.

Hispanic people, on the other hand, tend to be classified as lower on both warmth and competence, so we expected greater numbers of Hispanic workers to be found in occupations also classified as low on both warmth and competence.

We felt that our Model of Stereotype Incongruence may be perpetuated both by job seekers and decision makers through their own stereotype matching process.

Our Research
We recruited 55 U.S. residents (31 women) via Amazon’s Mechanical Turk. Participants were asked to list as many jobs and professions as possible within three minutes. A total of 546 occupations were generated. We combined similar and related occupations to yield a smaller set of broad categories (e.g., sheriff, cop, sergeant, and policeman were all classified as ‘police officer’).

Occupations were then categorized according to the nine job sectors defined by the Canadian National Occupational Classification system, and we included occupations that were listed by 10 or more participants. Our final set of occupations consisted of 60 job titles diversified across the labour market.

We then proceeded to classify these occupations based on the SCM. For this part of the study, participants were 1157 U.S. residents recruited via Amazon’s Mechanical Turk. Our questionnaire measured stereotypes about each occupation, and we examined stereotypes using scales that asked participants to rate occupations on warmth and competence. For warmth (six items: warm, good-natured, sincere, friendly, well-intentioned, trustworthy) and competence (six items: competent, capable, intelligent, efficient, skillful, confident), participants were asked how well a given word described each occupation (e.g., ‘Please indicate how well this word describes dentists’). The first step in the analyses involved computing the warmth and competence ratings for each occupation.

Finding: Ratings of warmth and competence were strongly correlated, suggesting the presence of an overall ‘halo bias’ when rating different occupations.

As the next step in our analysis, we sought to create a two-dimensional mapping of occupations by plotting them according to warmth and competence ratings. We found that occupations vary widely in terms of perceived warmth and competence. Some occupational groups are perceived to be warm, but not particularly competent (e.g., childcare, secretary, farmer); whereas others are perceived to be competent, but not particularly warm (e.g., lawyer, CEO). Unemployed individuals tend to be perceived as low on both warmth and competence, and other occupations fall in the middle when it comes to both dimensions (e.g., tech support worker, musician, police officer).

We also observed that individuals tend to agree more about ratings of competence and warmth for some occupations (e.g., firefighter, paramedic, pilot), but vary more in their ratings when it comes to others (e.g., lawyer, security guard, tech support worker). It is interesting to observe that participants sometimes agreed in terms of one dimension but were more divergent in their ratings of the other. For example, participants tended to agree in their ratings of doctors and dentists in terms of competence, but vary more in rating those occupational groups on warmth.

O*NET is a government funded program available to the general public, describing the attributes of hundreds of different jobs. It is the primary source of data about occupations in the U.S. economy, and is created using survey-based occupational ratings.

Given that O*NET provides well-established descriptions of occupations based on representative survey data, we expected to find that some of the occupational attributes identified within it would correspond with our classification of occupational stereotypes. O*NET includes an Interest Code for each occupation, categorizing it according to six different work environments: Realistic, Investigative, Artistic, Social, Enterprising, and Conventional. Realistic occupations (e.g., electrician, farmer, security guard) require physical strength, hands-on problem solving, and situations that require little interpersonal communication. Investigative occupations (e.g., computer programmer, dentist, doctor) are task-oriented and often mentally challenging.

Occupations that welcome self-expression (e.g., actor, musician, writer) are considered Artistic. Social professions (e.g., nurse, teacher, waiter) require strong communication skills and involve working closely with others. Occupations that require leadership and decision-making (e.g., CEO, manager, lawyer) are considered Enterprising and involve risk-taking. Lastly, Conventional occupations (e.g., accountant, librarian, postal worker) follow a clear set of rules and procedures.

To examine our data alongside the O*NET Interests, we obtained Interest Codes for 58 of our occupations.

Finding: Ratings of competence were positively correlated with jobs characterized as Investigative, and trended negatively with jobs characterized as Realistic and Conventional. Therefore, occupations that require employees to ‘think-through’ and carefully analyze problems are considered more competent than occupations requiring physical exertion or jobs that emphasize structure and order.

Ratings of warmth were positively correlated with jobs characterized as Social, and there was a negative trend with jobs characterized as Enterprising, and a positive trend with jobs characterized as Realistic. These results suggest that occupations perceived as highly warm involve close relationships with others or a concrete approach to problem solving (e.g., nurse, firefighter), whereas jobs requiring leadership and persuasion are seen as less warm (e.g., politician, lawyer).

The O*NET database also provides a summary of the Work Values satisfied by the occupation. Modeled from the Minnesota Importance Questionnaire, the six work values include: Achievement, Independence, Recognition, Relationships, Support, and Working Conditions. O*NET provides the top three work values that are met by each occupation.

Achievement occupations (e.g., actor, computer programmer, salesperson) are results oriented and satisfy a worker’s need to utilize his or her strongest abilities. Occupations satisfying the Independence value (e.g., electrician, engineer, chef) allow for creativity and employees often work individually. Occupations that provide Recognition (e.g., lawyer, pilot, CEO) are considered prestigious and offer advancement and leadership opportunities. Positions that fulfill the Relationship work value (e.g., bartender, cashier, bus driver) provide service to others in a non-competitive environment. Occupations with supportive management fulfill Support needs, whereas positions offering job security (e.g., librarian, medical assistant, welder) satisfy the Working Conditions value.

Similar to our analysis of the occupational interests, we coded for the presence of each work value for the same 58 occupations.

Finding: Ratings of competence were positively correlated with Achievement, Independence, and Recognition, and negatively correlated with work values related to Relationships and Support. These findings demonstrate that occupations involving highly motivated and goal-oriented employees are seen as more competent than jobs requiring ongoing support or supervision.

Turning to ratings of warmth, the results indicated a positive trend with work values related to relationships. Therefore, jobs that are seen as highly personable are also perceived to be warmer.

To determine whether incongruence between occupational and demographic stereotype content predicts occupational segregation, we then examined the composition of the U.S. labour force. We tested whether the ratings of warmth and competence of occupations in our classification would be positively associated with representativeness data of demographic groups (i.e., percentage employed in occupation), as obtained from U.S. national labor statistics, that are stereotypically congruent with those warmth and competence ratings. We expected that the congruence between demographic and occupational stereotypes along the dimensions of warmth and competence would be positively related to social representation within a given occupation.

Using data collected from the Current Population Survey (CPS) conducted by the U.S. Bureau of Labour Statistics, we obtained the annual average employment composition for 54 occupations examined in Study 1. Rates of unemployment for each demographic group were obtained from a separate report from the U.S. Bureau of Labor Statistics, but the unemployment composition was not available. Employment statistics about the military were obtained from the U.S. Department of Defense and employment information about politicians was obtained from the Congressional Research Service. Occupational warmth and competence ratings derived from Study 1 were correlated with representativeness data for each of the four demographic groups.

Our analyses revealed that each demographic group is better represented in occupations that are stereotypically congruent with their warmth and competence ratings. In terms of gender, jobs more commonly held by women (e.g., childcare worker, secretary, nurse) were perceived as warmer than jobs more commonly held by men (e.g., mechanic, plumber, pilot). Indeed, occupational warmth ratings were positively correlated with the percentage of female workers within a position.

Additionally, jobs more commonly held by women were trending to be perceived as less competent. Based on the available labour statistics, and consistent with a stereotype incongruence explanation, women were better represented in occupations that were rated higher on warmth and lower on competence.

Turning next to racial groups, Asian people, perceived as highly competent and mid-level in terms of warmth, were more highly represented in occupations related to science and math, which are also perceived as higher in competence and lower in warmth (e.g., scientist, computer programmer, engineer). Indeed, the percentage of Asian employees within an occupation was positively correlated with the stereotyped competence of the occupation.

Black individuals, who tend to be rated low on competence according to the literature on ambivalent stereotypes of blacks, were more highly represented in occupations located on the lower end of both warmth and competence (e.g., security guard, bus driver, taxi driver). Overall, we observed a strong negative correlation between the representation of black workers and the perceived competence of an occupation. Black people also had the highest unemployment rate in the U.S., and ‘unemployed’ was found to be the occupational group that is characterized as having the lowest warmth and competence levels.

Although stereotypes about Hispanic individuals are also characterized by low scores on competence and warmth according to the SCM), they were represented in occupations situated more centrally on both stereotype dimensions compared to Black workers (e.g., landscaper, construction worker, welder). Nonetheless, there were significantly fewer Hispanic employees working within fields characterized by higher levels of competence.   

Overall, representativeness statistics for various minority groups could be predicted from ratings of occupational warmth and competence. Interestingly, warmth emerged as an important predictor for gender representativeness, whereas competence emerged as an important predictor for representation of Asian, Black, and Hispanic workers. Conversely, occupational warmth was not correlated with representativeness of the racial groups examined in this study. These results supported our prediction that incongruence between occupational and demographic stereotypes is related to occupational segregation in today’s workplace.

Implications for Leaders
Our research has important implications for practitioners. As noted in the introduction, in an effort to combat the negative stereotypes about lawyers, the Ontario Bar Association’s marketing campaign has been focused on encouraging individuals to recognize lawyers’ competence. Our data demonstrate that such a campaign should be focused instead on highlighting the warmth-related functions of the legal profession.

Indeed, our data shows that lawyers have very little to gain in perceptions of competence (they already score at the top of that dimension), but a great deal to gain in perceptions of warmth (where they score among the lowest of all professions). Indeed, such a shift toward emphasizing the warmth-related aspects of the legal profession could have the added benefit of increasing the representation of women in that occupation.

Our classification could be effectively applied to similar campaigns across occupations, providing specific information about the aspects of the occupational stereotype that could stand to be improved. This approach could also be useful at the policy level whenever governments are seeking to increase enrolment in educational programs leading to careers with a projected labor shortage. Being aware of occupational stereotypes, how commonly they are held, and how they might be improved could even help to alleviate labor shortages.

Interventions aimed at strengthening the congruence between group stereotypes and desired occupations will be particularly important in increasing the representation of traditionally stigmatized groups in more positively perceived occupations. Our research can enable more focused interventions as it identifies where stereotype incongruence exists and what aspect of the stereotype needs to be addressed. These interventions around stereotype congruence may target multiple stages of the segregation processes.

For example, an intervention to increase the number of women in engineering at the recruitment stage may emphasize stereotypes around warmth rather than competence in marketing campaigns or job descriptions. Another possible intervention to increase selection of men and Asians for occupations in childcare is to provide selection criteria that emphasize requirements related to competence in additional to warmth.

Finally, at the promotion and performance appraisal stages, there could be interventions that emphasize warmth stereotypes and downplay the dominance of competence stereotypes in performance appraisal instruments and tools to increase the promotion and retention of women.

In closing
The stereotypes people hold of individuals carry over into the world of work, with significant implications for vocational choice, recruitment and selection. By understanding the structure of occupational stereotypes and their interaction with demographic stereotypes, we have shown how seemingly innocuous stereotypes have important implications for occupational segregation.


Joyce He is a PhD Candidate in Organizational Behaviour at the Rotman School of Management. Sonia Kang is an Associate Professor of Organizational Behaviour and HR Management in the Department of Management at the University of Toronto Mississauga, Chief Scientist at Behavioural Economics in Action at Rotman (BEAR) and a Research Fellow of the Rotman Institute for Gender and the Economy. Soo Min Toh is an Associate Professor of Organizational Behaviour & HR Management in the Department of Management at the University of Toronto Mississauga. Kaylie Tse is the Program Coordinator of Registrarial Services at the Rotman School of Management. This article is an adapted excerpt from their paper, “Stereotypes at Work: Occupational Stereotypes Predict Race and Gender Segregation in the Workforce”, which was published in the Journal of Vocational Behaviour.

[This article has been reprinted, with permission, from Rotman Management, the magazine of the University of Toronto's Rotman School of Management]