New research demonstrates that when affirmative action programs are used, the quality of the applicants increases.
Affirmative action is often criticized as giving unfair advantages. Different people are evaluated by different criteria, which inevitably lowers the quality of the selected group, is the claim.
Diversity achieved through intervention is quality-compromising diversity, says the critic.
The logic behind these claims is not hard to understand, but it may be wrong.
Imagine that 100 students are going to be admitted to a university. If the historical trend is that 70 of them are men and 30 of them are women, and if affirmative action is implemented to increase the number of women to 40, the claim of detractors would be that 10 men of higher quality are being left aside to bring in 10 women that otherwise would not have been selected.
One basic problem with this logic that I’ll leave aside here is the dubious assertion that a process resulting in 70 men and 30 women is fair; I’ve discussed that elsewhere, in Equality targets as a leadership tool and in a post I wrote for theglasshammer.com, Engaging CEOs in gender diversity.
There’s a more subtle problem with the claim that affirmative action compromises quality, and two recent articles in Science show that this claim is wrong.
In Ready, Steady, Compete, Marie Claire Villeval focuses on gender differences in competitions. This can be seen in sports, where ‘boys tend to outperform girls when racing against someone else, but not when running alone.‘ In other words, competition changes the relative performance, either enhancing the performance of boys or reducing the performance of girls.
If girls are not motivated by competition — if they in fact avoid it — then reducing competition might have a surprisingly different effect than compromising quality.
What if women — even highly qualified women — opt out when they perceive too much competition? What if reducing competition increases the willingness of women to participate?
When the level of competition is reduced, the hypothesis might go, high-performing women are increasingly likely to enter the competition. When they then win, it need not be at the cost of a higher-performing man; that man might only have won against a weaker pool.
A second Science article tests this hypothesis. In Affirmative action policies promote women and do not harm efficiency in the laboratory, Loukas Balafoutas and Matthias Sutter run 360 subjects through four different repetitions of an addition task, in which they solve as many math problems as they can in three minutes.
The first time they do it, they are rewarded for each correct calculation. The second time they do it, they are groups of six — three men and three women — and only the two best performers are rewarded. The third time they do it, they can choose if they want to do it individually — and be rewarded for each correct answer — or in a competition — and be rewarded more if they are one of two winners. The fourth time they all do it in a competition again, like in the second round.
Affirmative action is introduced in the third and fourth rounds. In the third round, before they choose whether they want to do the task individually or in a competition, the women are divided into five groups and given different information about the competition. In the fourth round, everyone competes, and again there are these five different groups and models.
- Group one is the control group; their competition is just like that in round 2.
- Group two has quotas added to the competition: there will be two winners, as in round 2, but one of them must be a woman. In practice, this means that the best performing woman will always win, even if that means a better performing man is prevented from winning.
- Group 3 experiences weak preferential treatment: when a man and a woman have the same score, the woman wins, and the equally well performing man may not. (Remember that there are two winners in each group. If a man and a woman tie for best, they both win in Group 3. But if a man and a woman tie for second best, then the woman joins the best performer as one of the two winners.)
- Group 4 experiences strong preferential treatment: when a woman’s score is just slightly less than a man’s, the woman still wins, and the man may not. (If the man was best and the woman next best, they both still win. If the man came in second and the woman was third, then she will win over him, if her score was very close to his.)
- Group 5 has a requirement that at least one woman is among the two winners, but the scores are not manipulated. If the result of the competition gives no woman among the winners, then the competition is repeated until one is. (This could be like a requirement to re-do a hiring or promotion process if no women are on the short-list.)
What do we learn from this study?
In the third round, when subjects choose if they want to be rewarded for individual performance or for winning a competition, the number of men choosing competition is twice the number of women doing so in group one, the control group, where there is no affirmative action.
But when there is affirmative action, the number of women choosing to participate in the competition increases; this is most dramatic for the weak and strong preferential treatment seen in groups 3 and 4.
In the control group, with no affirmative action, only 30% of the women chose competition over individual evaluation; with strong preferential treatment, 70% do.
Think about what this means: when they can choose, women are significantly more likely to enter into a competition when the possibility of affirmative action is in place. Not just weaker women; highly qualified women, too.
The impact of affirmative action on the combined talent of the group of winners could go in two directions. Affirmative action could lower the collective talent of the winners if better qualified men are passed over by worse qualified women.
But affirmative action could also increase the overall talent of the group of winners if better qualified women now enter the competition.
These women could then join the group of winners based on their performance alone; the affirmative action measure draws them into the competition, but gender-balanced results in the competition are achieved without actually intervening to change any results.
The large increase in competition entry by strong female performers shows the potential of policy interventions to improve the quality of participants. It is also encouraging to observe that strong male performers do not respond to policy interventions in a negative way.
The research shows that the average ability of the group of winners is higher with some forms of affirmative action. And in this particular study, the authors note that ‘hardly any better-qualified men were passed over as a result of interventions.’ For example, in group 5, where the competition is repeated until there is a woman among the winners, it was in fact never necessary to repeat the competition.
Finally, after the four rounds of doing this task, the group was given a task that measured cooperation. The groups that had completed round four with affirmative action showed no less cooperation than those in the control group, where there was no affirmative action. Furthermore, the winners and losers in the groups with affirmative action did not differ from one another in terms of how cooperative they were either. In short, the presence of affirmative action in a competition within a group did not negatively affect the ability of that group to subsequently perform cooperatively.
The claim that affirmative action, if implemented, necessarily lowers the quality of the selected group, is illogical. Indeed, the evidence from this study makes it clear that affirmative action for women as a policy can raise the overall quality of the winners without being unfair to the men.
What do these results mean for national and local policies? What do they mean for universities? I’d like to know your answers to these questions. I’ll be writing more soon with mine.
Photo courtesy of the Nordic Council of Ministries
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