The Implicit Association Test: An effective weapon against gender-based discrimination in science?

It is 2017, and despite the progress that has been made over the years in deconstructing stereotypes about women and science, 70% of women and men across 34 countries still regard science as a masculine domain, according to a finding of the Harvard Implicit Association Test. In this article, DiscovHER will explore how this test works, what its findings, particularly on gender bias in science, mean for female scientists in concrete terms, and how the test can be used to challenge these biases.

The Implicit Association Test (IAT), developed in 1998, is a scientific tool used in social psychology to measure the strength of an individual’s association between concepts or objects in memory. It has since been used to identify prejudices that individuals may not be aware of, or even if they are, that they avoid displaying in day-to-day life due to fear of judgement by members of their society. These biases vary from race, to sex, to age, and everything in between.

So, how does the test work? Essentially, test-takers are given two character traits on either side of a screen, then asked to associate an object or concept with either of these characteristics. For instance, in an IAT designed to measure racial bias, a test could have “white” on one side, and “black” on the other side, then an object, concept or characteristic in the middle of the screen, which the test-taker is then asked to associate with either “white” or “black”. In addition to examining to which characteristics or concepts individuals associate with each examined trait, the test also measures how long it takes for individuals to make these associations. In general, taking a longer time to associate concepts is said to be an indicator of implicit bias against the concept or person in question.

In the so-called progressive world that we live in today, it is very rare to come across explicit expressions of prejudice. However, just because these feelings are not openly expressed, that doesn’t mean that they don’t persist. What’s more, where they do, the consequences of these negative attitudes are dire for those to whom they are directed. For instance, the gender bias prevalent in the workplace often leads to women being paid less than their male counterparts, and having a lower chance of getting employed, especially if they are mothers (while the opposite is true for fathers in the professional world).

Within scientific circles, women face a constant devaluation of their research, and an even harder time breaking away from the role and perception of being nothing more than lab assistants. This prevents a significant number of female scientists from advancing their careers and research, something all of society pays a very high price for. As the Harvard study shows, they also face an additional invisible barrier of being implicitly associated with fields such as liberal arts, rather than science.

Why is this test important? The IAT’s objective of uncovering internalised prejudices could be the key to tackling them, especially in scientific circles where the assumption of rationality hinders scientists from assessing their own biases. In evaluating prejudices as something learned and not inherent to people, the test could go a long way into helping individuals in these circles overcome the societal shame of being prejudiced, and find a way to eradicate the effect of these biases at every step of the professional process. In doing so, we could prevent implicit prejudice from turning into explicit discrimination, thus creating the progressive, egalitarian environment we all yearn to live in.

Curious about the test? Try it out yourself here, and share your experience with us @4womeninscience.

For Women in Science

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