Gender Equality

Equality targets as a leadership tool

A decision to implement equality targets is a decision to pursue quality.

Equality targets should lead to increased gender balance. And increased gender balance leads to many improvements, such as employee satisfaction and, concomitantly, the productivity of the organization.

The concept of targets is the heir to the concept of quotas. And the claim that quotas feed quality is certainly not a familiar claim.

On the contrary, when I speak about the importance of achieving gender balance in research organizations, I often ask audiences to tell me what they think the most common objections to quotas are.

Can you imagine what kinds of answers I get?

  • Quotas are unfair because job applicants are judged by different criteria. Or, as a more dramatic audience recently put it, quotas are undemocratic.
  • When we use quotas and judge people by different criteria, the next objection goes, we inevitably hire someone of lower quality than we would if we didn’t have quotas.

Those are the two most common objections people come up with. Quotas are unfair, and they force us to compromise quality.

The importance of the role of the leadership of an organization in pursuing targets is reflected in some of the genSET recommendations and supported by the research identified in the genSET briefing materials, all of which is available at genderinscience.org.

Already in Recommendation 1 of the Consensus Report, for example, we emphasize the role of leaders who buy into the importance of the gender dimension of scientific work.

Quotas and targets are similar in that they both require identifying specific percentages to be achieved — maybe in hiring, maybe in promotion, maybe even, as I’ve recently argued, in the awarding of the Nobel Peace Prize — but they are both specific.

But they are different in that the failure to meet quotas has necessary consequences while the failure to meet targets in principle does not.

I think that’s a significant difference, and I don’t think I am doing anything inappropriate if I note that this was a major point of discussion in the Science Leaders panel in genSET.

When we talked about quotas, the possibilities for compromise seemed to be fewer than when we talked about other issues, such that it was clear early on that a proposal to use quotas would not have unanimous support on the panel.

We did find unanimous support however for a recommendation about targets.

Recommendation 12 reads: Explicit targets — and action plans to reach them — must be included in the overarching gender strategy of scientific institutions.

Using targets that are accompanied by action plans, also exposes an organization to the critiques about fairness and quality.

For example, part of Recommendation 11 states that if there are no women in the applicant pool, the positions should be re-advertised.

This would be a natural strategy to include in an action plan designed to achieve a target.

The University of Tromsø, in Norway, where I work, was the first university to adopt the genSET recommendations (European Commission Press Release) as part of its institutional policy. And as we pursue the strategies of genSET recommendations, we have to be prepared for essentially the same criticism as one meets when working with quotas.

How can we answer that criticism?

We might ask if it really is true that the supposedly radical solution of quotas, or even the less dramatic solution of targets, really does pull us away from a system that judges candidates by the same criteria, and if it really does force us to compromise quality.

We are fortunate that this topic has generated such interest that we no longer have to rely on anecdotes – that’s good because we all know that anecdotes don’t really tell us anything reliable anyway.

We have research on how evaluations are carried out, and we should explore that research and use it as the basis for policy decisions both within organizations and in governments.

I’m going to briefly mention three research articles, noting here just one highlight from each. I have much more to say about these articles and they topics they address, and if you’re interested, I invite you to visit my blog, where I write frequently on this topic, and where I refer to other publications I have on these matters. You’ll find it at curtrice.wordpress.com.

One of the most important studies is a paper called Nepotism and sexism in peer review, which Christine Wennerås & Agnes Wold published several years ago in Nature. Their project involved examining the evaluations of applications for postdoc positions in Sweden.

To do their project, they developed a method for comparing the CVs of applicants, especially for standardizing their publishing activity, so that it could be compared with the publishing activity of other applicants. And their discovery was that for a woman to be ranked by the reviewers as equally well-qualified as a man, she had to have 2.5 times as many publications as the man.

Is that an example of a democratic evaluation, of being judged by the same criteria?

Another important study is called The language of performance evaluations: gender-based shifts in content and consistency of judgement, which was published by Monica Biernat, M. J. Tocci and Joan C. Williams this year in the journal Social, Psychological and Personality Science.

These three researchers analyze the performance evaluations of junior attorneys in a Wall Street law firm. Those performance evaluations have two elements: a numerical score and also a brief prose narrative.

The research project explores the relationship between the prose narrative and the scores given in these evaluations. Overall, the men as a group scored higher numerically than the women, when the evaluation was done by male supervisors. But when they used prose, these same supervisors either made evaluations that did not distinguish men from women, or they made evaluations which favored the women.

The authors actually look quite a bit more closely at the topics addressed in the narratives, looking for the types of descriptions that correlated with higher numerical scores. Men got higher numerical scores when they were described as having high competence on technical matters. Women were not rewarded for technical mastery of their field. Instead, they were rewarded for interpersonal warmth — and, of course, their numerical scores were harmed when they did not meet the expectations of such warmth.

Again, is this what it means to be judged by the same criteria?

The third and final study I want mention is called The Paradox of Meritocracy in Organizations, which was published by Emilio Castilla and Stephan Benard in the Administrative Science Quarterly last year.

The context for this article is a little different than the first two I’ve mentioned, and this one is especially important because it addresses the critique of pursuing targets in a very important way.

Imagine a critique of an organization and a plan to use targets, that says: Instead of spending so much energy establishing targets and figuring out how to achieve them, why don’t we instead try to build a culture of fairness in our organization? Why don’t we instead of risking a compromise of quality, instead of risking unfairness, why don’t we rather make sure the we achieve a true meritocracy at our workplace?

In short, let’s not focus on targets, let’s focus on transparency, one might say.

It turns out that this isn’t quite as straightforward as we might have hoped, as Castilla and Benard make almost horrifyingly clear.

Their article presents the results of three experiments in which 445 subjects with managerial experience are asked to evaluate the file of fictitious employees at a fictitious company and make recommendations about bonuses, promotions and terminations.

They manipulate of course the sex of the employees, leaving the rest of the file the same. But they also manipulate something about the company. In particular, they sometimes make a point of emphasizing the meritocratic nature of the company, and they sometimes don’t. The companies they describe either have as a core corporate value that they emphasize merit in evaluations, or else they don’t have that value.

And then they write this: “The main finding is consistent across the three studies: when an organization is explicitly presented as meritocratic, individuals in managerial positions favor a male employee over an equally qualified female employee by awarding him a larger monetary reward.” This is what they call the paradox of meritocracy.

Much of their article is devoted to discussing how this works, and there, too, there is much research to build on. They note, for example, that we now know that when people are led to believe that they are unbiased, fair or objective, that they in fact are more likely to behave in biased ways. An individual who is allowed to explicitly disagree with some sexist statements will then in experimental hiring scenarios, tend to recommend a male over a female candidate, to paraphrase.

The paradox of meritocracy in organizations is a complex study and we have to think very carefully about the conclusions we should draw from this. It seems, however, that the explicit pursuit of meritocratic organizational values is not equivalent with increased fairness. On the contrary, it seems to create greater imbalances.

This research suggests that gender balance should not be pursued by focusing on the creation of a culture of fairness, but by something else. Targets, perhaps?

From my perspective, these three articles tell us something about our current system and about the direction we need to move. And they are very interesting in the context of the stereotypes that we usually encounter about quota systems.

For me, this kind of research, and the scores of articles cited in the references of these works and elsewhere, force a conclusion about the alleged incompatibility of quality and quotas. Actually, they force one of two conclusions, and at this point, I’m not sure which one is right, so I’ll tell you both and you help me figure this out.

One possible conclusion is that the stereotypes about quota-systems are exactly wrong. It’s not in quota-systems that people are judged by different criteria; it’s not in quota-systems that quality must defer to other criteria, where one of the important other criteria is sex. So, from this perspective, the stereotypes are the opposite of what is true.

The alternative conclusion is that the stereotypes about quota-systems are exactly right. Quota-systems are by definition ones in which people are judged by different criteria; they are by definition ones in which quality must yield.

And as we have seen, that is a description of the status quo. That is a description of the system we have today. That is a description which requires us to conclude that our present system is a quota-system. Of course, it’s not women who are the beneficiaries of the current quotas. It’s men.

Equality targets are a different kind of management tool than quotas. And it may be the case that the word quota has such strong associations to injustice that it may be useful to stop using it.

But ultimately, a leadership approach which actually uses targets — as opposed to merely setting them — is going to meet the same criticisms. The approach is going to be seen as unfair and as compromising quality.

And in the face of that situation, we have to know what we really think. We have to know if these charges are true. And we should base our views on this question on the research that investigates it.

When we do that, we see that we have nothing like a fair system today, and that quality often yields to other factors. When we see that, we know that other approaches are necessary. And when we study the benefits of other approaches — the benefits of setting targets — we know that other approaches are important.

This is the text of my talk from the first European Gender Summit.

My interest in moving universities towards balance encompasses gender equality, the communication of scientific results, promoting research-based education and leadership development more generally. Read more

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