Skip to main content
SpringerLink
Log in

Racial Stereotype Endorsement, Academic Engagement, Mindset, and Performance among Black and White American Adolescents

  • Empirical Research
  • Published:
Journal of Youth and Adolescence Aims and scope Submit manuscript

Abstract

The role of racial stereotypes in youth’s academic achievement becomes salient during adolescence. Yet, very few studies have investigated whether associations between Black and White American adolescents’ stereotype endorsement and their cognitive engagement, mindset beliefs, and performance in math differed by stereotype valence (i.e., positive versus negative) and youth gender. To address these gaps, this 3-year longitudinal study (n = 2546; age range = 11–16; 50% males, 60% White, 40% Black; 57% qualified for free lunch) investigated (a) whether Black and White American adolescents’ endorsement of positive and negative racial stereotypes differentially related to their cognitive engagement, ability mindset, and math performance and (b) whether gender moderated these relations. The results revealed that endorsing either negative or positive racial stereotypes (as opposed to those with unbiased beliefs) was linked to lower cognitive engagement and stronger fixed mindsets in math 1 year after, while endorsing negative racial stereotypes was linked to lower math scores. In addition, the intersection of adolescents’ race and gender moderated some of the observed effects. The inverse link between negative stereotype endorsement and math cognitive engagement was significant for Black girls but not for Black boys. The positive link between negative stereotype endorsement and fixed math ability mindset was stronger for Black girls than Black boys, whereas the link was stronger for White boys than White girls. These findings shed light on the direction and strength of the links between racial stereotype valence and math outcomes among Black and White youth.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

Notes

  1. To ensure students had sufficient knowledge about other groups to gauge their math abilities relative to their own, we focused on Black and White students, as these two groups best reflected the schools’ racial composition.

References

  • Augoustinos, M., & Rosewarne, D. L. (2001). Stereotype knowledge and prejudice in children. British Journal of Developmental Psychology, 19(1), 143–156.

    Article  Google Scholar 

  • Autor, D., Figlio, D., Karbownik, K., Roth, J., & Wasserman, M. (2016). Family disadvantage and the gender gap in behavioral and educational outcomes [Working Paper]. Institute for Policy Research, Northwestern University. http://www.ipr.northwestern.edu/publications/docs/workingpapers/2015/IPR-WP-15-16.pdf.

  • Beyer S. (1999). The accuracy of gender stereotypes. Sex Roles, 40, 787–813.

    Article  Google Scholar 

  • Bian, L., Leslie, S. J., & Cimpian, A. (2017). Gender stereotypes about intellectual ability emerge early and influence children’s interests. Science, 355, 389–391.

    Article  PubMed  Google Scholar 

  • Bieg, M., Goetz, T., Wolter, I., & Hall, N. C. (2015). Gender stereotype endorsement differentially predicts girls’ and boys’ trait-state discrepancy in math anxiety. Frontiers in Psychology, 6, 1404.

  • Blackwell, L. S., Trzesniewski, K. H., & Dweck, C. S. (2007). Implicit theories of intelligence predict achievement across an adolescent transition: A longitudinal study and an intervention. Child Development, 78, 246–263.

    Article  PubMed  Google Scholar 

  • Boaler, J. (2016). Mathematical Mindsets; Jossey-Bass: San Francisco, CA, USA.

  • Brody, G. H., Yu, T., & Beach, S. R. H. (2016). Resilience to adversity and the early origins of disease. Development and Psychopathology, 28(4, Pt. 2), 1347–1365.

    Article  PubMed  PubMed Central  Google Scholar 

  • Burnett, M., Kurtz-Costes, B., Vuletich, H. A., & Rowley, S. J. (2020). The development of academic and nonacademic race stereotypes in African American adolescents. Developmental Psychology, 56, 1750–1759. https://doi.org/10.1037/dev0001071.

    Article  PubMed  Google Scholar 

  • Cheryan, S., & Bodenhausen, G. V. (2000). When positive stereotypes threaten intellectual performance: The psychological hazards of “Model Minority” status. Psychological Science, 11(5), 399–402.

    Article  PubMed  Google Scholar 

  • Chestnut, E., Lei, R., Leslie, S.-J., & Cimpian, A. (2018). The myth that only brilliant people are good at math and its implications for diversity. Education Sciences, 8, 65.

    Article  Google Scholar 

  • Cokley, K. O. (2002). Ethnicity, gender, and academic self-concept: A preliminary examination of academic disidentification and implications for psychologists. Cultural Diversity and Ethnic Minority Psychology, 8(4), 378–388.

    Article  PubMed  Google Scholar 

  • Copping, K. E., Kurtz‐Costes, B., Rowley, S. J., & Wood, D. (2013). Age and race differences in racial stereotype awareness and endorsement. Journal of Applied Social Psychology, 43(5), 971–980.

    Article  PubMed  PubMed Central  Google Scholar 

  • Copur-Gencturk, Y., Cimpian, J. R., Lubienski, S. T., & Thacker, I. (2020). Teachers’ bias against the mathematical ability of female, Black, and Hispanic students. Educational Researcher, 49, 30–43.

    Article  Google Scholar 

  • Cunningham, M., Swanson, D. P., & Hayes, D. M. (2013). School‐ and community‐based associations to hypermasculine attitudes in African American adolescent males. American Journal of Orthopsychiatry, 83(2-3), 244–251. https://doi.org/10.1111/ajop.12029.

    Article  PubMed  Google Scholar 

  • Cvencek, D., Nasir, N. S., O'Connor, K., Wischnia, S., & Meltzoff, A. N. (2014). The development of math-race stereotypes: They say Chinese people are the best at math. Journal of Research on Adolescence, 25(4), 630–637.

    Article  Google Scholar 

  • Cvencek, D., Nasir, N. I. S., O’Connor, K., Wischnia, S., & Meltzoff, A. N. (2015b). The development of math–race stereotypes: “They say Chinese people are the best at math”. Journal of Research on Adolescence, 25, 630–637. https://doi.org/10.1111/jora.12151.

    Article  Google Scholar 

  • Dasgupta, N., & Asgari, S. (2004). Seeing is believing: Exposure to counterstereotypic women leaders and its effect on the malleability of automatic gender stereotyping. Journal of Experimental Social Psychology, 40(5), 642–658.

    Article  Google Scholar 

  • Degol, J. L., Wang, M.-T., Zhang, Y., & Allertoin, J. (2018). Do growth mindsets in math benefit females? Identifying pathways between gender, mindset, and motivation. Journal of Youth and Adolescence, 47, 976–990.

    Article  PubMed  Google Scholar 

  • Del Toro, J., & Wang, M.-T. (2020). School cultural socialization and academic performance: Examining ethnic-racial identity development as a mediator among youth of color. Child Development, 1, 1–19.

    Google Scholar 

  • Devine, P. G. (1989). Stereotypes and prejudice: Their automatic and controlled components. Journal of Personality and Social Psychology, 56(1), 5–18. https://doi.org/10.1037/0022-3514.56.1.5.

    Article  Google Scholar 

  • Dweck, C. S. (2006). Mindset: The new psychology of success. New York, NY: Random House.

  • Eccles, J. S. (2009). Who am I and what am I going to do with my life? Educational Psychologist, 44, 78–89.

    Article  Google Scholar 

  • Evans, A. B., Copping, K. E., Rowley, S. J., & Kurtz-Costes, B. (2011). Academic self-concept in Black adolescents: Do race and gender stereotypes matter? Self and Identity, 10(2), 263–277.

    Article  PubMed  PubMed Central  Google Scholar 

  • Ferguson, R. F. (2003). Teachers’ perceptions and expectations and the Black-White test score gap. Urban Education, 38, 460–507.

    Article  Google Scholar 

  • Fischer. (2010). A longitudinal examination of the role of stereotype threat and racial climate on college outcomes for minorities at elite institutions. Social Psychology of Education: An International Journal, 13(1), 19–40.

    Article  Google Scholar 

  • Francis, D. V., de Oliveira, A. C. M., & Dimmitt, C. (2019). Do school counselors exhibit bias in rec ommending students for advanced coursework? The B. E. Journal of Economic Analysis & Policy, 19 (4). https://doi.org/10.1515/bejeap-2018-0189.

  • Glock, S., & Klapproth, F. (2017). Bad boys, good girls? Implicit and explicit attitudes toward ethnic minority students among elementary and secondary school teachers. Studies in Educational Evaluation, 53, 77–86.

    Article  Google Scholar 

  • Gocłowska, M. A., Crisp, R. J., & Labuschagne, K. (2013). Can counter-stereotypes boost flexible thinking? Group Processes & Intergroup Relations, 16(2), 217–231.

    Article  Google Scholar 

  • Haimovitz, K., & Dweck, C. S. (2017). The origins of children’s growth and fixed mindsets: New research and a new proposal. Child Development, 88(6), 1849–1859.

    Article  PubMed  Google Scholar 

  • Hamaker, E. L., Kuiper, R. M., & Grasman, R. P. P. P. (2015). A critique of the cross-lagged panel model. Psychological Methods, 20(1), 102–116. https://doi.org/10.1037/a0038889.

    Article  PubMed  Google Scholar 

  • Hanson, S. L. (2007). Success in science among young African American women. Journal of Family Issues, 28(1), 3–33.

    Article  Google Scholar 

  • Hartley, B. L., & Sutton, R. M. (2013). A stereotype threat account of boys’ academic underachievement. Child Development, 84, 1716–1733.

    Article  PubMed  Google Scholar 

  • Henry, D. A., Betancur-Cortés, L., & Votruba-Drzal, E. (2020). Black-white skills disparities differ by family socioeconomic status from early childhood through early adolescence. Journal of Educational Psychology, 112(8), 1471–1489.

    Article  Google Scholar 

  • Holland, M. M. (2012). Only here for the day: The social integration of minority students at a majority White high school. Sociology of Education, 85, 101–120.

    Article  Google Scholar 

  • Huguley, J. P., Wang, M.-T., Vasquez, A., & Guo, J. (2019). Parental ethnic-racial socialization practices and the construction of children of color’s ethnic-racial identity: A research synthesis and meta-analysis. Psychological Bulletin, 145, 437–458.

    Article  PubMed  Google Scholar 

  • Hwang, N., Reyes, M., & Eccles, J. S. (2019). Who holds a fixed mindset and whom does it harm in mathematics? Youth & Society, 51, 247–267.

    Article  Google Scholar 

  • King, D. K. (1992). Unraveling Fabric, Missing the Beat: Class and Gender in Afro-American Social issues. The Black Scholar, 22, 36–44.

    Article  Google Scholar 

  • Leslie, S.-J., Cimpian, A., Meyer, M., & Freeland, E. (2015). Expectations of brilliance underlie gender distributions across academic disciplines. Science, 347(6219), 262–265.

    Article  PubMed  Google Scholar 

  • Lorenz, G. (2021). Subtle discrimination: do stereotypes among teachers trigger bias in their expectations and widen ethnic achievement gaps? Social Psychology of Education, 1, 1–35.

    Google Scholar 

  • Lyons, E. M., Simms, N., Begolli, K. N., & Richland, L. E. (2017). Stereotype threat effects on learning from a cognitively demanding mathematics lesson. Cognitive Science, 42, 678–690.

    Article  PubMed  Google Scholar 

  • Macnamara, B. N., & Rupani, N. S. (2017). The relationship between intelligence and mindset. Intelligence, 64, 52–59.

    Article  Google Scholar 

  • McClendon, C., & Wigfield, A. (1998). Group differences in African American adolescents’ achievement-related beliefs about math and science: An initial study. Journal of Black Psychology, 24, 28–43.

    Article  Google Scholar 

  • McKown, C., & Strambler, M. J. (2009). Developmental antecedents and social and academic consequences of stereotype-consciousness in middle childhood. Child Development, 80(6), 1643–1659.

    Article  PubMed  Google Scholar 

  • McNeish, D., Stapleton, L. M., & Silverman, R. D. (2017). On the unnecessary ubiquity of hierarchical linear modeling. Psychological methods, 22, 114–140. https://doi.org/10.1037/met0000078.

    Article  PubMed  Google Scholar 

  • Miller, R. S., & Wang, M.-T. (2019). Cultivating adolescents’ academic identity: Ascertaining the mediating effects of motivational beliefs between classroom practices and mathematics identity. Journal of Youth and Adolescence, 48, 2038–2050.

    Article  PubMed  Google Scholar 

  • Munter, C., & Haines, C. (2019). Mathematics teachers’ enactment of cognitively demanding tasks and students’ perception of racial differences in opportunity. Mathematical Thinking and Learning, 21, 155–177.

    Article  Google Scholar 

  • Nasir, N. I. S., McKinney de Royston, M., O’Connor, K., & Wischnia, S. (2016). Knowing about racial stereotypes versus believing them. Urban Education, 52(4), 491–524.

    Article  Google Scholar 

  • National Science Foundation. (2018). Women, Minorities, and Persons with Disabilities in Science and Engineering: 2011. Arlington, Va.: National Science Foundation.

  • Noguera, P. A. (2008). The trouble with Black boys:… And other reflections on race, equity, and the future of public education. San Francisco, CA: John Wiley & Sons.

  • Okeke, N. A., Howard, L. C., Kurtz-Costes, B., & Rowley, S. J. (2009). Academic race stereotypes, academic self-concept, and racial centrality in African American youth. Journal of Black Psychology, 35(3), 366–387.

    Article  PubMed  Google Scholar 

  • Osborne, J. W. (1997). Race and academic disidentification. Journal of Educational Psychology, 89(4), 728–735.

    Article  Google Scholar 

  • Oswald, F. L., Mitchell, G., Blanton, H., Jaccard, J. & Tetlock, P. E. (2015). Using the IAT to predict ethnic and racial discrimination: Small effect sizes of unknown societal significance. Journal of Personality and Social Psychology, 108, 562–571.

    Article  PubMed  Google Scholar 

  • Oyserman, D., & Destin, M. (2010). Identity-based motivation: Implications for intervention. The Counseling Psychologist, 38, 1001–1043.

    Article  PubMed  PubMed Central  Google Scholar 

  • Park, J. Z., Martinez, B. C., Cobb, R., Park, J. J., & Wong, E. R. (2015). Exceptional outgroup stereotypes and White racial inequality attitudes toward Asian Americans. Social Psychology Quarterly, 78(4), 399–411.

    Article  PubMed  PubMed Central  Google Scholar 

  • Paunesku, D., Walton, G. M., Romero, C., Smith, E. N., Yeager, D. S., & Dweck, C. S. (2015). Mind-set inter ventions are a scalable treatment for academic under achievement. Psychological Science, 26, 784–793. https://doi.org/10.1177/0956797615571017.

    Article  PubMed  Google Scholar 

  • Pennington, C. R., Heim, D., Levy, A. R., & Larkin, D. T. (2016). Twenty years of stereotype threat research: A review of psychological mediators. PLoS ONE, 11(1), e0146487.

    Article  PubMed  PubMed Central  Google Scholar 

  • Plante, I., de la Sablonnière, R., Aronson, J. M., & Théorêt, M. (2013). Gender stereotype endorsement and achievement-related outcomes: The role of competence beliefs and task values. Contemporary Educational Psychology, 38(3), 225–235.

    Article  Google Scholar 

  • Plante, I., O’Keefe, P. A., Aronson, J., Fréchette-Simard, C., & Goulet, M. (2019). The interest gap: How gender stereotype endorsement about abilities predicts differences in academic interests. Social Psychology of Education: An International Journal, 22(1), 227–245.

    Article  Google Scholar 

  • Priest, N., Walton, J., White, F., Kowal, E., Baker, A., & Paradies, Y. (2014). Understanding the complexities of ethnic-racial socialization processes for both minority and majority groups: A 30-year systematic review. International Journal of Intercultural Relations, 43, 139–155.

    Article  Google Scholar 

  • Reardon, S. F., Fahle, E. M., Kalogrides, D., Podolsky, A., & Zárate, R. C. (2019). Gender Achievement Gaps in U.S. School Districts. American Educational Research Journal, 56(6), 2474–2508. https://doi.org/10.3102/0002831219843824.

    Article  Google Scholar 

  • Reyna, C. (2000). Lazy, dumb, or industrious: When stereotypes convey attribution information in the classroom. Educational Psychology Review, 12(1), 85–110.

    Article  Google Scholar 

  • Riegle-Crumb, C., Morton, K., Nguyen, U., & Dasgupta, N. (2019). Inquiry-based instruction in science and mathematics in middle-school classrooms: examining its association with students’ attitudes by gender and race/ethnicity. AERA Open, 5, 1–17.

    Article  Google Scholar 

  • Riegle‐Crumb, C., Moore, C., & Ramos‐Wada, A. (2011). Who wants to have a career in science or math? Exploring adolescents’ future aspirations by gender and race/ethnicity. Science Education, 95(3), 458–476.

    Article  Google Scholar 

  • Rowley, S. J., Kurtz-Costes, B., & Rouland, K. (2013). Self views of African American youth are related to the gender stereotypes and academic attributions of their mothers. Self Identity, 12, 382–399. https://doi.org/10.1080/15298868.2012.682360.

    Article  PubMed  Google Scholar 

  • Rowley, S. J., Kurtz‐Costes, B., Mistry, R., & Feagans, L. (2007). Social status as a predictor of race and gender stereotypes in late childhood and early adolescence. Social Development, 16(1), 150–168.

    Article  Google Scholar 

  • Schmader, T., Johns, M., & Barquissau, M. (2004). The costs of accepting gender differences: The role of stereotype endorsement in women’s experience in the math domain. Sex Roles: A Journal of Research, 50, 835–850.

    Article  Google Scholar 

  • Schmader, T., Johns, M., & Forbes, C. (2008). Anintegrated process model of stereotype threat effects on performance. Psychological Review, 115(2), 336–356.

    Article  PubMed  PubMed Central  Google Scholar 

  • Shih, M., Pittinsky, T. L., & Ho, G. C. (2012). Stereo type boost: Positive outcomes from the activa tion of positive stereotypes. In M. Inzlicht & T. Schmader (Eds.), Stereotype threat: Theory, process and application (pp. 141–158). New York, NY: Oxford University Press.

  • Sun, K. L. (2018). The role of mathematics teaching in fostering student growth mindset. Journal for Research in Mathematics Education, 49(3), 330–355.

    Article  Google Scholar 

  • Swanson, D. P., Cunningham, M., & Spencer, M. B. (2003). Black males’ structural conditions, achievement patterns, normative needs and “opportunities”. Urban Education, 38(5), 608–633.

    Article  Google Scholar 

  • Varelas, M., Martin, D. B., & Kane, J. M. (2012). Content learning and identity construction: A framework to strengthen African American students’ mathematics and science learning in urban elementary schools. Human Development, 55, 319–339.

    Article  Google Scholar 

  • Vining-Brown, S. (1994). Minority women in science and engineering education. Final Report. Princeton, NJ: Educational Testing Service.

  • Walton, G. M., & Cohen, G. L. (2003). Stereotype lift. Journal of Experimental Social Psychology, 39(5), 456–467.

    Article  Google Scholar 

  • Wang, M.-T., & Eccles, J. S. (2013). School context, achievement motivation, and academic engagement: A longitudinal study of school engagement using a multidimensional perspective. Learning and Instruction, 28, 12–23.

    Article  Google Scholar 

  • Wang, M.-T., Degol, J. L., & Henry, D. A. (2019). An integrative development-in-sociocultural-context model for children’s engagement in learning. American Psychologist, 74, 1086–1102.

    Article  PubMed  Google Scholar 

  • Wang, M.-T., Guo, J., & Degol, J. S. (2019). The role of sociocultural factors in student motivation in mathematics and language arts: A cross-cultural review. Adolescent Research Review, 1, 1–16.

    Google Scholar 

  • Wang, M.-T., Hofkens, T. L., & Ye, F. (2020). Classroom quality and adolescent learning in mathematics: A multi-method, multi-informant perspective. Journal of Youth and Adolescence, 49, 1987–2002.

    Article  PubMed  Google Scholar 

  • Wang, M.-T., Smith, L. V., Huguley, J. P., & Miller-Cotto, D. A. (2020). Parental ethnic-racial socialization and children of color’s academic success: A meta-analytic review. Child Development, 91, 528–544.

    Google Scholar 

  • Wang, M.-T., Fredricks, J. A., Ye, F., Hofkens, T. L., & Schall, J. (2016). The math and science engagement scale: Scale development, validation, and psychometric properties. Learning and Instruction, 43, 16–26.

    Article  Google Scholar 

  • Wang, M.-T., Binning, K. R., Del Toro, J., Qin, X., & Zepeda, C. (2020). Skill, thrill, and will: The role of metacognition and motivation in predicting student engagement over time. Child Development, 1, 1–20.

    Google Scholar 

  • Wang, M.-T., Henry, D. A., Smith, L. V., Huguley, J. P., & Guo, J. (2020). Parental ethnic-racial socialization practices and children of color’s psychosocial and behavioral adjustment: A systematic review and meta-analysis. American Psychologist, 75, 1–22.

    Article  PubMed  Google Scholar 

  • Wang, M.-T., Zepeda, C., Qin, X., Del Toro, J., & Binning, K. R. (2021). More than growth mindset: Individual and interactive links among socioeconomically disadvantaged adolescents’ ability mindsets, metacognitive skill, and math engagement. Child Development, 92, 957–976.

    Google Scholar 

  • Wang, M.-T., Zepeda, C., Qin, X. Del Toro, J., & Binning, K. R. (2021). More than growth mindset: Individual and interactive links among socioeconomically disadvantaged adolescents’ abilitymindsets, metacognitive skill, and math engagement. Child Development, 92, 957–976.

    Google Scholar 

  • Wang, M.-T., Ye, F., & Degol, J. L. (2017). Who chooses STEM careers? Using a relative cognitive strength and interest model to predict careers in science, technology, engineering, and mathematics. Journal of Youth and Adolescence, 46, 1805–1820.

    Article  PubMed  Google Scholar 

  • Woodcock, A., Hernandez, P. R., Estrada, M., & Schultz, P. W. (2012). The consequences of chronic stereotype threat: Domain disidentification and abandonment. Journal of Personality and Social Psychology, 103(4), 635–646. https://doi.org/10.1037/a0029120.

    Article  PubMed  PubMed Central  Google Scholar 

  • Wu, W., Selig, J. P., & Little, T. D. (2012). Longitudinal models. In T. D. Little (Ed.), Oxford handbook of quantitative methods (Vol. 2, pp. 387–410). New York, NY: Oxford University press.

  • Yeager, D. S., & Dweck, C. S. (2012). Mindsets that promote resilience: When students believe that personal charac teristics can be developed. Educational Psychologist, 47, 302–314. https://doi.org/10.1080/00461520.2012.722805.

    Article  Google Scholar 

Download references

Author information

Author notes

  1. These authors contributed equally: Daphne A. Henry, Wei Wu, Juan Del Toro

  2. These authors jointly supervised this work: Daphne A. Henry, Wei Wu, Juan Del Toro

Authors and Affiliations

  1. University of Pittsburgh, 230 South Bouquet Street, Pittsburgh, PA, 15213, USA

    Ming-Te Wang, Juan Del Toro & James P. Huguley

  2. Boston College, Chestnut Hill, Boston, MA, USA

    Daphne A. Henry

  3. Indiana University-Purdue University Indianapolis, Indianapolis, IN, USA

    Wei Wu

Authors
  1. Ming-Te Wang
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Daphne A. Henry
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Wei Wu
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Juan Del Toro
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. James P. Huguley
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

M.T.W. conceived of the study (e.g., study questions, study design, literature review, result interpretation, development of the writing outline), and drafted and revised the manuscript; D.A.H. participated in the result interpretation and drafted the discussion section; W.W. performed the data analysis, participated in the interpretation of the data, and drafted the analytic strategy and result sections; J.D.T. performed the data analysis, assisted with the literature review, and drafted part of the literature review section. J.P.H. reviewed the draft and provided feedback on the revision. All authors read and approved the final manuscript.

Data Sharing and Declaration

The datasets generated and/or analyzed during the current study are not publicly available but are available from the corresponding author on reasonable request.

Corresponding author

Correspondence to Ming-Te Wang.

Ethics declarations

Conflict of Interest

The authors declare no competing interests.

Ethical Approval

All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards. A review conducted by the Institutional Review Board approved the study to be consistent with the protection of the rights and welfare of human subjects and to meet the requirements of the Federal Guidelines.

Informed Consent

Informed consent was obtained from all individual participants included in the study.

Additional information

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Wang, MT., Henry, D.A., Wu, W. et al. Racial Stereotype Endorsement, Academic Engagement, Mindset, and Performance among Black and White American Adolescents. J Youth Adolescence 51, 984–1001 (2022). https://doi.org/10.1007/s10964-022-01587-4

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10964-022-01587-4

Keywords

Search

Navigation