The project implicit international dataset: Measuring implicit and explicit social group attitudes and stereotypes across 34 countries (2009-2019)

Abstract

For decades, researchers across the social sciences have sought to document and explain the worldwide variation in social group attitudes (evaluative representations, e.g., young-good/old-bad) and stereotypes (attribute representations, e.g., male-science/female-arts). Indeed, uncovering such country-level variation can provide key insights into questions ranging from how attitudes and stereotypes are clustered across places to why places vary in attitudes and stereotypes (including ecological and social correlates). Here, we introduce the Project Implicit:International (PI:International) dataset that has the potential to propel such research by offering the first cross-country dataset of both implicit (indirectly measured) and explicit (directly measured) attitudes and stereotypes across multiple topics and years. PI:International comprises 2.3 million tests for seven topics (race, sexual orientation, age, body weight, nationality, and skin-tone attitudes, as well as men/women-science/arts stereotypes) using both indirect (Implicit Association Test; IAT) and direct (self-report) measures collected continuously from 2009 to 2019 from 34 countries in each country's native language(s). We show that the IAT data from PI:International have adequate internal consistency (split-half reliability), convergent validity (implicit-explicit correlations), and known groups validity. Given such reliability and validity, we summarize basic descriptive statistics on the overall strength and variability of implicit and explicit attitudes and stereotypes around the world. The PI:International dataset, including both summary data and trial-level data from the IAT, is provided openly to facilitate wide access and novel discoveries on the global nature of implicit and explicit attitudes and stereotypes.

Keywords: Cross-cultural data; Explicit attitudes; Implicit Association Test; Implicit attitudes; Project Implicit.

Fig. 1

Total sample size by country across tasks. Yellow colors indicate larger samples, blue colors indicate smaller samples. Countries without data shown in white. Note: The data for the US are available separately (see PI:US).

Fig. 2

Country differences in implicit attitudes across six IAT tasks. Y-axes represent Cohen’s d effect sizes from one-sample tests against μ = 0. X-axes list the countries, ranked from left to right in order from strongest to weakest IAT D scores. Error bars represent 95% confidence intervals around Cohen’s d estimates.

Fig. 3

Country differences in explicit attitudes across six tasks (Likert measures). Y-axes represent Cohen’s d effect sizes from one-sample tests against μ = 0, using seven-point Likert scales (with 0 indicating neutral attitudes). X-axes list the countries, ranked from left to right in order from strongest to weakest explicit attitudes. Error bars represent 95% confidence interval limits around Cohen’s d estimates.

Fig. 4

Country differences in explicit attitudes across six tasks (thermometer measures). Y-axes represent Cohen’s d effect sizes from one-sample tests against μ = 0, from 21-point combined thermometer scales (with 0 indicating neutral warmth/coldness toward both groups). X-axes list the countries, ranked from left to right in order from strongest to weakest explicit attitudes. Error bars represent 95% confidence interval limits around Cohen’s d estimates.

Fig. 5

Country differences in implicit and explicit Gender–Science stereotypes. Y-axes represent Cohen’s d effect sizes from one-sample tests against μ = 0 for Implicit Association Test D scores (panel 1), explicit attitudes toward science and humanities measured from ten-point combined Likert scales (with 0 indicating neutral attitudes toward both domains; panel 2), and explicit stereotypes associating science with men and arts with women from 14-point combined Likert scales (with 0 indicating neutral stereotypes; panel 3). X-axes list the countries, ranked from left to right in order from strongest to weakest attitudes and stereotypes. Error bars represent 95% confidence interval limits around Cohen’s d estimates.