European map of Implicit Racial Bias
This map shows how easily White Europeans in Europe associate black faces with negative ideas. Each country’s colour reflects the average Implicit Association Test (IAT) score for that country using data from Harvard’s Project Implicit. Overall we have scores for 288,076 White Europeans, collected between 2002 and 2015, with sample sizes for each country shown inset. Blue shows low levels of racial bias, and red shows high levels – with Europe’s peaks in countries like the Czech Republic and other East European nations.
The results shown in this map give detail to what we already expected – that across Europe racial attitudes are not neutral. Blackness has negative associations for White Europeans, and there are some interesting patterns in how the strength of these negative associations vary across the continent.
*open data, open tools*
This new map is possible because Project Implicit release their data via the Open Science Framework (osf.io). This site allows scientists to share the raw materials and data from their experiments, allowing anyone to check their working, or re-analyse the data (as we have done here). The data analysis and map were done in R, an open source statistical programming language, and we collaborated using github.com, a platform for software projects. Now the data and code to produce the map are shared on Figshare.com, a site which allows data and graphics to be given stable digital object indentifiers (DOIs) and so integrated into the scholarly literature like other publications. We believe that open tools and publishing methods like these are necessary to make science better and more reliable.
The data comes from Europeans who visited the US Project Implicit website, which is in English. Language specific IAT data may be available in the near future. For now we can be certain that the sample reflects a subset of the European population which are more internet-savvy than typical, probably younger, and probably more cosmopolitan (both because they are both comfortable using a website in English, and from the sheer fact that they were interested in taking a test of implicit racism). These factors are likely to underweight the extent of implicit racism in each country.
This data reflects scores on just one IAT (the classic White-Black/Positive-Negative IAT). Other dimensions of social attitudes can be assessed by different IATs. You can explore these at Project Implicit https://implicit.harvard.edu/implicit/
The idea of implicit bias is introduced and explained in this video
Peanut Butter, Jelly and Racism by Saleem Reshamwala in The New York Times
We were inspired to make this map of US IAT scores by Chris Mooney in the Washington Post “Across America, whites are biased and they don’t even know it”
Useful recent summaries of some of the controversies around the IAT are
Can We Really Measure Implicit Bias? Maybe Not by Tom Bartlett January 05, 2017 for Chronicle of Higher Education.
Psychology’s Favorite Tool for Measuring Racism Isn’t Up to the Job by Jesse Singal for the New York Magazine / Science of Us, 11 January 2017.
The IAT was developed in the 1990s by Anthony Greenwald and colleagues:
Greenwald, A. G., McGhee, D. E., & Schwartz, J. L. (1998). Measuring individual differences in implicit cognition: the implicit association test. Journal of personality and social psychology, 74(6), 1464.
You can read scholarly reviews of the test here
Nosek, B. A., Greenwald, A. G., & Banaji, M. R. (2007). The Implicit Association Test at age 7: A methodological and conceptual review. Automatic processes in social thinking and behavior, 265-292.
Greenwald, A. G., Poehlman, T. A., Uhlmann, E. L., & Banaji, M. R. (2009). Understanding and using the Implicit Association Test: III. Meta-analysis of predictive validity. Journal of personality and social psychology, 97(1), 17-41.
Greenwald, A. G., Banaji, M. R., & Nosek, B. A. (2015). Statistically small effects of the Implicit Association Test can have societally large effects. Journal of Personality and Social Psychology, 108(4), 553-561
The reference for the data we adapt is
Xu, K., Nosek, B. & Greenwald, A.G., (2014). Psychology data from the Race Implicit Association Test on the Project Implicit Demo website. Journal of Open Psychology Data. 2(1), p.e3. DOI: http://doi.org/10.5334/jopd.ac
Relevant papers by ourselves include
Holroyd, J., Scaife, R., Stafford, T. (in press). Responsibility for Implicit Bias. Philosophy Compass.
Stafford, T. (2014). The perspectival shift: how experiments on unconscious processing don’t justify the claims made for them. Frontiers in Psychology, 5, 1067. doi:10.3389/fpsyg.2014.01067
More about our work on bias mitigation here
Code and raw data here github.com/georgeg0/WorldBias
George Gittu collated and cleaned the data, coded and refined the map. Tom Stafford helped with some analysis decisions and wrote this text. Tom Stafford was part funded by a Leverhulme Trust grant on implicit bias 2014-2017, and is grateful both to the Trust and his project partners, Jules Holroyd (PI) and Robin Scaife for introducing him to the literature on implicit bias. Thanks also to Frank Xu, Brian Nosek and Colin Smith at Project Implicit.