Martha Cooper: Using Motivational Psychology to Understand Implicit Racial Bias

My name is Martha Cooper, and I am a junior majoring in Psychology and Philosophy here at FSU. For the past year, I have been working in Dr. Irmak Okten’s research lab studying motivated social cognition. Developing skills in data collection and analysis has greatly improved my confidence in myself and my academic abilities. It has also equipped me with the necessary skills to investigate my own independent research interests, which I will be doing for this project. After completing my undergraduate degree at FSU, I plan on pursuing a graduate degree in Social Psychology. My end goal is to become a professor to teach and conduct research at a public university. I am interested in conducting further research in bias reduction, as well as intellectual humility. Both of these areas significantly shape how we interact with members of minority groups and how open we are to having conversations about highly polarized issues.

Martha Cooper, Junior, Psychology and Philosophy

My IDEA Grant project is focused on assessing motivational dimensions like perceived value and self-efficacy expectancy in individuals to predict their implicit racial bias. Ultimately, I want to establish this relationship to one day create a bias reduction intervention that reduces implicit bias by promoting relevant expectancies. This project will also set the foundation for my Honors in the Major project, which will assess the impact of intellectual humility on different forms of bias.

I have been passionate about bias awareness for quite some time, but have often felt frustrated and powerless as blatant displays of racial bias continue to take place with no end in sight. Doing research in social cognition has shown me how I can productively address bias, and hopefully one day reduce it. I am also excited to work on a project that synthesizes ideas from my two majors: I will be formally assessing the dimensions that underlie prejudice (social psychology), but also informally assessing the moral implications of my findings (philosophy).

 This May, I will create a survey using the Bias Reduction Motivation scale to measure individuals’ expectancies in the context of bias reduction. More specifically, I will assess perceived importance (do people value being unbiased?), self-efficacy expectancy (do people think they can be unbiased?) and outcome expectancy (do people think the target of bias will perceive them as being prejudiced?). I will measure implicit racial bias using the Harvard Implicit Association Test. The IAT provides a subtle way of measuring negative biases towards minority groups that many people are unaware they possess.

The IAT can measure implicit attitudes towards Blacks specifically by detecting automatic evaluation of different stimuli. The stimuli being used in my version will be Black and White faces paired with pleasant and unpleasant adjectives. So, someone who continues to quickly pair unpleasant adjectives with Black faces would be rated high in implicit racial bias.

After data collection, I will examine the correlation between scores on the IAT and where individuals fall on each motivational dimension of bias reduction. I predict that people high in implicit racial bias will have significantly low self-efficacy expectancies. In other words, I anticipate that people who do not think they are capable of behaving in an unbiased manner will be more prone to having negative mental associations regarding targets of bias. If I can establish this relationship, that will be a major step towards creating an eventual bias reduction intervention.

After analyzing my data in July, I will begin creating my research poster in August. I will present this poster in September with my fellow IDEA Grant recipients. Overall, I anticipate to grow as a young researcher this summer by independently collecting and analyzing data. I am particularly looking forward to data analysis, where I will finally learn if my hypothesis was accurate, and if motivational dimensions are a significant way to understand implicit racial bias.

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