Implicit-explicit discrepancies regarding racial attitudes among U.S. Whites

ABSTRACT

Work on implicit attitude measures has become increasingly rich and nuanced, with much theoretical development emanating from investigations of the correspondence between implicit and explicit attitude measures. However, various facets of implicit-explicit discrepancies (IEDs) remain underexplored – particularly, how prevalent the potentially distinct categories of IEDs are. Existing models speak mainly to discrepancies that occur because explicit attitudes are less prejudiced than implicit attitudes and tends to assume other possible categories are trivial. Using data from two large samples, this study provides a descriptive analysis of the different ways IEDs exist regarding racial attitudes among U.S. Whites. Results suggest IEDs exist largely in line with traditional theories, but there is substantial variation yet to be understood. These results were robust across a variety of measures, although decision-making in the construction of measures can be consequential. Future research should consider this variation in theory development regarding implicit versus explicit attitude measures.

KEYWORDS:

• American National Election Study
• implicit cognition
• implicit-explicit correspondence
• implicit-explicit discrepancies
• PI

Disclosure statement

No potential conflict of interest was reported by the author.

Data availability statement

The data described in this article are openly available in the Open Science Framework at https://doi.org/10.1080/00224545.2023.2195992.

Open scholarship

This article has earned the Center for Open Science badges for Open Data and Open Materials through Open Practices Disclosure. The data and materials are openly accessible at https://doi.org/10.1080/00224545.2023.2195992

Supplemental data

Supplemental data for this article can be accessed online at https://doi.org/10.1080/00224545.2023.2195992

Notes

1. I use the terms “Anti-Black” and “Pro-Black” here as interchangeable with the terms “Pro-White” and “Anti-White” (respectively), but it should be noted that this is some ways an oversimplification, as some work has shown being anti-Black can have distinct consequences from being pro-White (e.g., Blanton et al., 2006; Dovidio & Gaertner, 2000). However, for the purposes of identifying “unexpected categories” of IEDs, we are just interested in relative black versus white differences, and so this distinction is less necessary. Therefore, we use the simpler, 9-category classification.

2. The terms “more prejudiced” and “less prejudiced” are probably more appropriate here given these measures tap levels of prejudiced attitudes, but the terms “Anti-Black” and “Pro-Black” are used here simply to maintain consistency with labels for other variables.

3. The decision to use .25 SDs was arbitrary, as there is no agreed upon cutoff point in existing literature for when we would identify a score as “biased.” As such, I tested the sensitivity of all results to different cutoff points (.15 and .50 SDs) and found that, although the percentages for different categories changes somewhat by definition, there were no drastic differences in findings across a reasonable range of cutoffs. Analyses using all cutoffs are available on the OSF web site (https://doi.org/10.17605/OSF.IO/3FX5R).

4. We nonetheless ran analyses using buffers for explicit measures and found this made some difference in how many respondents are categorized as Neutral for more direct measures such as the feeling thermometers, direct evaluations, and stereotypes, which is unsurprising given how many respondents score exactly neutral on these measures. These results are presented in the Supplemental Information on the project’s OSF web site.

5. Although being “Pro-Black” on the racial resentment, modern racism, and Attitudes Toward Blacks scales was more common, this category did not actually gauge favoring Black people but instead just reflected being below the median of that prejudice measure.

Additional information

Funding

The author(s) reported there is no funding associated with the work featured in this article.

Notes on contributors

Frank J. Gonzalez

Frank J. Gonzalez is an Assistant Professor in the School of Government and Public Policy at the University of Arizona. His research focuses on political cognition and the pyschology of inequality, with particular attention to race and class inequality.