Meritocracy, bias, and success: reward and recognition for diverse groups

Developing reward and recognition systems for the diverse individuals that make up successful groups could boost access to fair credit, writes Eugenie Hunsicker

I have been involved in diversity initiatives in the sciences for decades. During this time, there have been tremendous efforts in many areas, with particular improvements in policies relating to returning from maternity leave and flexible working. An Athena Swan initiative to celebrate the advancement of gender equality in higher education institutions has also put pressure on departments to consider carefully how all aspects of the work environment should be improved for gender equity.

But progression of women to the top academic ranks has remained stubbornly and depressingly low. In my home discipline of mathematics, the proportion of the professoriate who are women has increased in the UK from 6% in 2011 to 11% in 2016 – a large proportional increase, but overall, still nowhere near parity. 

In a recent conversation about gender diversity in UK universities, one colleague mentioned that, at her university, they had analysed how long it would take the institution to reach gender parity among the professoriate based on continuing with current practices. They discovered that due to having far fewer female academic applicants, a slower rate of female promotion, and greater female turnover, the answer was ‘never’. 

Surely, significant change is an imperative within higher education. Similar stories emerge from business, with the proportion of (white) women managers in US companies with more than 100 employees remaining constant at 29% since 2000, according to a 2016 Harvard Business Review article.

Within academia, promotion has traditionally been based on an individual’s ability to secure funding for, and publish, research. When we look at these factors, we see right away why women are still struggling to reach the highest levels at the same rate as men: they neither publish as much nor obtain research funding in the same quantities as male counterparts (according to an Elsevier report on research performance through the lens of gender, and analysis of data from the UK’s Engineering and Physical Sciences Research Council, respectively).  

On average, women simply don’t measure up in the standard metrics. Some of this is likely to be due to unequal burdens in areas other than research – an issue that universities can – and should – continue to address. But, even given equal research time, as a woman in science, it’s hard not to feel that the deck is stacked against you subtly in ways that individual universities cannot change. 

This is the frustrated mindset I found myself in a year ago when a colleague pointed me to the ‘No heroes’ blog by the London School of Economics philosopher, Liam Kofi Bright. The blog starts: ‘I am opposed to meritocracy,’ which, at first, was a shock to me. After all, surely meritocracy is the right system. But a few hours reading the papers cited there opened my eyes, and meritocracy has become my rant of the year.

Meritocracy

The term ‘meritocracy’ was coined by sociologist, Michael Young, in his satirical 1958 book, The Rise of the Meritocracy. In a 2001 column for the Guardian, he describes his horror at the current use of the word as a positive. He writes: ‘It is good sense to appoint individual people to jobs on their merit. It is the opposite when those who are judged to have merit of a particular kind harden into a new social class without room in it for others… It is hard indeed in a society that makes so much of merit to be judged as having none. No underclass has ever been left as morally naked as that.’

These ideas were taken up again in an article by the author, philosopher and former management consultant, Matthew Stewart, in a 2018 article for The Atlantic, which echoes Young’s ideas: ‘The meritocratic class has mastered the old trick of consolidating wealth and passing privilege along at the expense of other people’s children.’ 

Specifically, the problem with merit as a means of judging individuals is not in its generic usage, but rather when ‘merit’ becomes hardened into a particular set of criteria, the design and award of which are controlled by those who are deemed to already have it, and which are then used to limit inclusion in the new meritocracy.   

Bias

Both Young and Stewart are primarily concerned here with meritocracy as a means of reinforcing class division. But social class is not the only line along which privilege is divided, and reward systems focused on merit have been shown to convey benefit or disadvantage along the lines of gender and race.

In their groundbreaking 2010 paper, ‘The Paradox of Meritocracy in Organisations’, MIT Sloan Management Professor, Emilio Castilla, and Indiana University Sociology Professor, Stephen Bernard, investigated ‘whether gender and racial inequality persists in spite of management’s efforts to promote meritocracy or even because of such meritocratic efforts’. 

They carried out a study in which individuals in managerial positions were asked to make decisions about bonus pay for various employee profiles. They manipulated the gender of the employees in these profiles, as well as whether the company’s core values emphasised meritocracy in evaluations and compensation. They found that, when primed with ‘non-meritocratic’ company values, men and women were given equal bonuses, on average – $399.66 USD for men and $401.66 USD for women. However, when primed with ‘meritocratic’ company values, men were given an average bonus of $420.10 USD, compared to women’s $374.02 USD.  

Castilla and Bernard point to two possible explanations for this phenomenon. One is that, in contexts in which people are primed to believe that they are unbiased, fair or objective, studies have found that they are more likely to behave in biased ways. For instance, when individuals have been given the opportunity to disagree with sexist statements, and therefore establish their credentials as unbiased individuals, they are more likely, subsequently, to choose a male candidate over a female one.    

The second explanation relates to the idea that when people feel more objective, they become more confident that their beliefs are valid, as demonstrated in a 2007 paper co-authored by INSEAD’s Eric Luis Uhlmann
(then at Northwestern University’s Kellogg School of Management) and Stanford GSB’s Geoffrey Cohen (then at the University of Colorado, Boulder).

Blind orchestra auditions and their effect on the proportions of women hired is a well-known example in work on bias and diversity (see box on page 32). Iris Bohnet from the Harvard Kennedy School has pointed out, in an interview for the Harvard Business Review, that moves towards blind auditions met with resistance from orchestra directors: ‘Note that this [change in proportion of women] didn’t result from changing mindsets. In fact, some of the most famous orchestra directors at the time were convinced that they didn’t need curtains because they, of all people, certainly focused on the quality of the music and not whether somebody looked the part. The evidence told a different story.’

Lauren Rivera, Professor at Northwestern University’s Kellogg School of Management, has investigated another mechanism through which an emphasis on merit can in fact result in biased decisions, described in the 2015 book, Pedigree. In a study in which she observed discussions in a firm after the first round of interviews, she found that different demographic groups were subjected to greater scrutiny with regards to different aspects of merit. 

For example, the mathematical skills of women, together with those defined as ‘black’, were much more often questioned than those defined as ‘Indian’ or ‘white men’. Among candidates who made minor mistakes in mathematics, women were rejected for not having the right skills, while men were given a pass, with interviewers assuming they were having an ‘off’ day.  

The same effect is reflected in academia. In a 2017 study of publications in economics, University of Liverpool Lecturer, Erin Hengel, found that, in measures of readability, papers by women in economics journals score 1-6% better than those authored by men, and that the readability of papers by women increases over their careers, while that of those authored by men does not. 

Furthermore, by comparing pre-released versions of papers with published versions, she determined that peer review is directly responsible for about half of this difference. With the additional burden of scrutiny placed on women authors, their lower publication rate can be seen as a result of bias demonstrated by the ‘guardians’ of publishing – referees already among the subject elite – in their judgement of the merit of works submitted.

The success of groups

Recently, there has been considerable work on the benefits of diversity to the success of organisations. The 2015 McKinsey report, Diversity Matters, found that companies in the top quartile for gender diversity were 15% more likely than companies in the bottom quartile to have financial returns above the national median in their industry, and that companies in the top quartile for racial and ethnic diversity were 35% more likely. 

In academia, the majority of published work is collaborative, and studies have shown that in some areas, co-authored papers are more likely to be published in top journals and more likely to be cited. Interestingly, studies by Anita Wooley of Carnegie Mellon University’s Tepper School of Business have shown that the success of groups is not very strongly correlated to individual measures of intelligence (which are correlated to individual success). Wooley and her colleagues found that group success was better predicted by such measures as social sensitivity, turn-taking and the proportion of women in the group.    

However, as is pointed out by the University of Arizona’s Justin Bruner (then at the Australian National University) and Cailin O’Connor, a Professor at the University of California, Irvine, in their 2015 paper, ‘Power, Bargaining and Collaboration’, although success comes from the work of groups, rewards for successful work, such as promotion and raises, accrue to individuals.Their paper demonstrated a model to show how the hierarchical structure of academia can, in particular, lead to the disadvantage of underrepresented groups in bargaining for the credit for group success. Indeed, most individuals viewed by society as exceptionally successful, such as Bill Gates, are seen this way in large part due to society crediting them with the success that is, in fact, the work of a large group. History is rife with examples of individuals, such as Rosalind Franklin (DNA) and Katherine Johnson (Apollo programme) whose critical contribution to group successes have been credited to others who were in a better social position to claim them.  

This suggests one way forward that addresses the difficulties we experience due to a focus on meritocracy (which generally focuses on individuals and on particular characteristics, such as educational success, which are known to be socially linked). That way is to work on developing reward and recognition systems for the diverse individuals that make up successful groups. 

This would involve broad awareness of everyone who contributes to a group and the formulation of reward and recognition systems that provide fairer access to credit for its less prestigious members. This is a difficult challenge, but one that promises both a more equitable treatment of all who contribute, and increased success through the ability to attract and retain more diverse teams to meet the complex challenges that modern society poses.

Eugenie Hunsicker is a data scientist at Loughborough University, where she is also the Director for Equality and Diversity in the School of Science.

She is involved with equality, diversity and inclusion work at a national level, as the Chair of the Women in Mathematics Committee of the London Mathematical Society, Deputy Chair of the Athena Forum and a member of the steering group of the Women in Data Science and Statistics special interest group at the Royal Statistical Society. 

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