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Measuring racial essentialism in the genomic era: The genetic essentialism scale for race (GESR)

Abstract

Racial essentialism is the belief that races are biologically distinct groups with defining core “essences,” a notion associated with increased social distance and racial bias. While there are different kinds of racial essentialism, understanding and measuring genetic essentialism – the belief that racial groups and their defining core essences are determined by genes – is increasingly important in the wake of the Human Genome Project and the genomic revolution that it spurred. Many have questioned whether such genomic advances will reinforce genetic essentialist beliefs about race, but scholarly research is limited by measures that do not specify the role of genes in these beliefs or allow for distinct theoretical sub-components. In this paper, we develop and validate the Genetic Essentialism Scale for Race (GESR) using a sequential transformative mixed methods approach. Data for analysis come from an original survey-based study with a sample of 1069 White native-born Americans. We employ both exploratory factor analysis and confirmatory analysis to derive and confirm a three-factor model of genetic essentialism (category determinism, core determinism, and polygenism). Due to the high correlation between these factors, we also test for a second-order measurement model with three first-order factors. After conducting additional reliability, validity, and construct validity testing, we propose the GESR— a second-order construct with three first-order dimensions— as a reliable measure of genetic essentialism. The GESR will allow researchers to determine the impact of new genetic developments like race-based medicines and genetic ancestry testing on genetic essentialist beliefs about race.

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Notes

  1. 1.

    Similarly, with regard to race, Byrd and Hughey (2015) differentiate between the concept that genes determine fixed, innate racial categories, and the belief that those racial categories have core essences that determine their character and behavior. They refer to these constructs as biological determinism and genetic essentialism, respectively, but argue that while distinct, these beliefs are frequently intertwined. We use different terminology to emphasize that these are both dimensions of genetic essentialism.

  2. 2.

    The item referring to biology states “To a large extent, a person’s race biologically determines his or her abilities.” The others include: “Although a person can adapt to different cultures, it is hard if not impossible to change the disposition of a person’s race.”; “How a person is like (e.g., his or her abilities, traits) is deeply ingrained in his or her race. It cannot be changed much.”; and “A person’s race is something very basic about them and it can’t be changed much.” (Chao et al. 2013).

  3. 3.

    A second item states “Different racial groups are all basically alike ‘under the skin’” (reverse scored) which is ambiguous; people could interpret it as referring to genetics, but others may see it as consistent with psychological essentialism or belief that essential differences are located in the soul.

  4. 4.

    We use the term “polygenism” rather than speciation as this belief may not go as far as to believe that races are different human species. Nonetheless, there is considerable overlap between our dimension of polygenism and Tawa’s (2017) dimension of speciation. We use this terminology because it reflects a long-established belief system that has been well documented (Jackson and Weidman 2005). However, it should not be confused with the term “polygenetic,” a description of traits that result from a number of genes.

  5. 5.

    See Online Supplement for further details of the study design. Because our development and analysis of the GESR uses the pre-test data only, and does not distinguish the Treatment and Control groups, the experimental nature of the original study is incidental to the analysis in this paper.

  6. 6.

    The p value is 0.31 for the test without the covariates, and close to 1 for CDM, so we fail to reject the null hypothesis that the variables are missing completely at random.

  7. 7.

    Polychoric correlation coefficients are maximum likelihood estimates of the product-moment correlation among the underlying normally distributed variables.

  8. 8.

    We are presenting here only the three-factor solution because our final model is a three-factor model. In the first stage, we explored two, four and five-factor models, which also show similar patterns. However, the items with high uniqueness scores were weaker on theoretical grounds, and screeplot, parallel analysis, and model comparisons were all supportive of a three-factor solution.

  9. 9.

    For the subsample with complete data, using these 9 items, the KMO score is .819, and the Bartlett’s test of sphericity indicates a chi-square value of 401.233 with 36 degrees of freedom. Both tests confirm that subsample with complete data has enough observations with interrelated variables to proceed with factor analysis. See Online Supplement for tables using this subsample.

  10. 10.

    We also ran the models with asymptotic distribution free estimation, and the results remained the same.

  11. 11.

    Our measure of political inclination uses feelings thermometer questions on a scale from 0 to 10 to rate how favorable or warm respondents feel toward the Republican Party and toward the Democratic Party. Their response toward Democrats is subtracted from their response toward Republicans in this measure.

  12. 12.

    Participants were asked how often they had a conversation with someone from a different racial group (Black, Asian, Hispanic/Latino, Middle Eastern/Arab, or Native American) in the past six months. Response options ranged on a 7-point scale from “not at all” to “every day.” From these 5 variables, we created a variable of mean frequency of interracial contact with any of these racial groups in the past six months.

  13. 13.

    Please refer to the Online Supplement for how to generate the scale in a structural model.

  14. 14.

    For further information on the number of categories in agree-disagree scales, see Revilla et al. (2014).

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Acknowledgements

The authors would like to thank Qiang Fu, Steven Heine, Catherine Lee, Ann Morning, Nathan Roberson, Brian O’Connor, and Charmaine Royal. This research was funded by grants from the Social Sciences and Humanities Research Council of Canada (#435-2014-0467), the Canada Foundation for Innovation (#23744), and the UBC Killam Faculty Research Fellowship.

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Correspondence to Şule Yaylacı.

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Yaylacı, Ş., Roth, W.D. & Jaffe, K. Measuring racial essentialism in the genomic era: The genetic essentialism scale for race (GESR). Curr Psychol 40, 3794–3808 (2021). https://doi.org/10.1007/s12144-019-00311-z

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Keywords

  • Genetic essentialism
  • Racial essentialism
  • Scale
  • Race
  • Racial conceptualization
  • Second-order factor model