Science Publications

Sign Up
Sign In
Submit
Journal of Biomedical and Life Sciences
Cite This Article Share Download PDF XML
  1. Home
  2. Journals
  3. Journal of Biomedical and Life Sciences
  4. Archive
  5. Volume 4, Issue 2, 2024
  6. Article
Article Open Access November 19, 2024

The Cost of Opportunity: Anti-Black Discrimination in High Resource Settings

Shervin Assari 1, 2, 3, 4,* and Hossein Zare 5, 6
1
Department of Internal Medicine, Charles R. Drew University of Medicine and Science, Los Angeles, CA, United States
2
Department of Family Medicine, Charles R. Drew University of Medicine and Science, Los Angeles, CA, United States
3
Department of Urban Public Health, Charles R. Drew University of Medicine and Science, Los Angeles, CA, United States
4
Marginalization-Related Diminished Returns (MDRs) Center, Los Angeles, CA, United States
5
Department of Health Policy and Management, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, United States
6
School of Business, University of Maryland Global Campus (UMGC), Adelphi, MD, United States
Publihed in: Journal of Biomedical and Life Sciences (Volume 4, Issue 2, 2024)
Page(s): 92-110
DOI: 10.31586/jbls.2024.1128
Received
July 30, 2024
Revised
September 27, 2024
Accepted
November 12, 2024
Published
November 19, 2024
Keywords
: Racial Disparities; Educational Outcomes; School Discrimination; School Discipline; Childhood Opportunity Index; Academic Achievement; Black-White Achievement Gap
Creative Commons

This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.
Copyright: Copyright © The Author(s), 2024. Published by Scientific Publications

Abstract

Objective: Inequalities exist in children’s educational outcomes—including reading proficiency, school discrimination, and school disciplinary actions—across zip codes with different levels of educational childhood opportunity index (COI). This study examines the interaction between race and educational environment on children’s educational outcomes. We hypothesize that race, parental education, and their interaction are associated with perceived school discrimination, which in turn reduces their cognitive, academic, and emotional wellbeing. We also hypothesize that Black children with high socioeconomic status (SES) report high perceived school discrimination in high-COI settings. Methods: Data were drawn from the Adolescent Brain Cognitive Development (ABCD) study, which measures a wide range of educational, cognitive, and emotional outcomes. At the same time, the ABCD children are sampled across areas with vast differences in COI rankings, that can be classified into these five categories: very high, high, average, low, and very low educational COIs. Our structural equation models (SEM) tested the additive and interactive effects of race and educational attainment on perceived school discrimination, and the effects of school discrimination on various cognitive abilities (reading proficiency, picture vocabulary, and list sorting working memory), school suspension, as well as depressed mood. Our multi-group SEM assessed how these relationships vary across educational COI levels. Results: Our findings showed that high SES Black children report highest school discrimination in residential areas with highest COIs. This is based on the observation that the interaction between race and parental education on experiences of school discrimination were only significant in areas with highest COI. Across residential areas with different COI levels, students who experienced higher school discrimination had higher suspension, worse depression, and worse cognitive performance. Conclusion: While higher COIs are associated with better academic outcomes, Black-White gaps exist in the role of increased COI through increased racial bias that children perceive. These findings underscore the complexity of educational equity, suggesting that improving COI alone is insufficient for eliminating racial disparities in school experiences. Policies should be in place to reduce school-based discrimination against Black students in high COI settings.

1. Introduction

Racial disparities in educational outcomes have persisted across generations in the United States, perpetuating cycles of inequality [1, 2]. These gaps hinder the future success of Black students and contribute to broad societal disparities, including economic and health inequities [3, 4]. Educational achievement is a primary predictor of socioeconomic mobility, making these disparities particularly consequential [5]. For instance, differences in academic performance led to unequal access to higher education, a critical gateway to economic success and social mobility [6, 7, 8]. As a result, Black students disproportionately encounter barriers in college admissions, job opportunities, and long-term economic stability [6, 7, 8, 9, 10, 11, 12].

Extensive research across fields—education, economics, psychology, and sociology—has examined the root causes of racial gaps in education [13]. Scholars have identified various structural factors that disadvantage Black children, such as limited access to quality educational resources [14, 15]. The historical legacies of Jim Crow laws, segregation, and slavery have left enduring impacts, with Black and White communities often residing in vastly different environments. White neighborhoods are generally more affluent, while Black communities more frequently experience poverty, unemployment, and higher crime rates [16, 17, 18]. These environmental disparities create unequal educational opportunities [19], further compounded by systemic issues such as underfunded schools and inadequate educational resources in predominantly Black areas [19, 20, 21, 22, 23].

Family background, including parental education, family involvement, and marital status, also influences children's educational outcomes [24, 25, 26], though these factors themselves are shaped by broader environmental inequalities rooted in structural racism [27, 28, 29, 30, 31, 32, 33]. While some controversial claims suggest that genetic factors may contribute to these disparities [34], a substantial body of evidence indicates that environmental factors, particularly access to educational opportunities, are the primary drivers of these inequities [35, 36, 37, 38, 39, 40].

Research by scholars such as Luthar [41, 42, 43] and Assari [44] complicates the narrative by suggesting that highly resourced environments—particularly affluent, predominantly White areas—do not always lead to better outcomes for all groups of children. Luthar’s work shows that high-pressure, competitive environments in affluent areas can negatively impact both minority and White youth [41, 42, 4345, 46, 47, 48, 49]. In parallel, Assari’s research suggests that in high-opportunity settings, Black students experience heightened levels of discrimination [50, 51, 52, 53, 54, 55, 56, 57, 58], which in turn undermines their academic performance [59, 60, 61].

Building on this emerging literature, the current study explores the paradoxical effects of high Childhood Opportunity Index (COI) areas on Black students, particularly those from high socioeconomic status (SES) backgrounds [59, 60, 61]. We hypothesize that in residential areas with higher COI, Black students, especially those from higher SES families, are more likely to perceive and experience school-based discrimination. This perceived school discrimination, in turn, is expected to diminish their academic achievements despite the apparent advantages of growing up in a high-opportunity environment. In essence, we extend the framework of "Minorities’ Diminished Returns" [62], which posits that structural racism, segregation, and social stratification reduce the returns of SES for Black children. Specifically, we hypothesize that affluent educational environments may exacerbate biases against Black students, limiting the educational and cognitive benefits they might otherwise gain from their socioeconomic position [63].

2. Methods

2.1. Setting and Design

This study utilized data from the Adolescent Brain Cognitive Development (ABCD) study, a large-scale, longitudinal dataset designed to explore the factors influencing children’s brain development, cognitive functioning, and educational outcomes. The ABCD study is a national longitudinal study, drawing from a diverse population of children across the United States. It collects comprehensive data on participants' family socioeconomic status (SES), neighborhood characteristics, academic performance, and neuroimaging data related to brain development. The ABCD data is particularly well-suited for examining how environmental and contextual factors—such as educational opportunity—shape cognitive and educational outcomes across diverse groups.

2.2. Measures
2.2.1. Moderator (Strata)

Educational Child Opportunity Index (COI): Educational COIs were measured using residential data that capture local school quality, the availability of educational resources, and access to academic enrichment opportunities in the neighborhood. This measure is based on the COI available in the ABCD dataset, which reflects the broader social and educational context in which children are raised. Higher educational COI values indicate greater access to high-quality educational opportunities. For this analysis, educational COI was treated as a five-level ordinal variable, categorized into very high, high, average, low, and very low educational opportunity.

2.2.2. Predictors

Race: Race was self-reported by the participants or their guardians and was dichotomized into Black and White for the purposes of this study. This dichotomization was necessary to explore specific racial disparities in educational outcomes and school experiences.

Parental Education: Parents were asked: Participants were asked, “What is the highest grade or level of school you have completed or the highest degree you have received?”. The same question was asked for the education of partner/spouse. Responses were 0 = never attended/kindergarten only; 1 = 1st grade; 2 = 2nd grade; 3 = 3rd grade; 4 = 4th grade 4; 5 = 5th grade; 6 = 6th grade 6; 7 = 7th grade 7; 8 = 8th grade; 9 = 9th grade; 10 = 10th grade 10; 11 = 11th grade; 12 = 12th grade; 13 = high school graduate; 14 = GED or equivalent diploma; 15 = some college; 16 = associate degree: occupational; 17 = associate degree: academic program; 18 = Bachelor’s degree (ex. BA); 19 = Master’s degree (ex. MA); 20 = professional school degree (ex. MD); and 21 = Doctoral degree. This variable was transformed into Jaeger education coding [64] that ranges from 31 to 46. A higher score indicated higher educational attainment.

Race x Parental Education: We used multiplicative effect of race (0 vs. 1) and Jaeger education coding (ranges from 31 to 46). The variable was 0 for all White children and Jaeger education coding for Black students.

2.2.3. Mediator

Perceived School Discrimination: Perceived school discrimination was assessed through student self-reports using a series of items designed to capture discriminatory experiences within the school setting. These items included questions about unfair treatment by teachers or peers based on race or ethnicity, as shown in Box 1. Response options were coded as 0 for "No" and 1 for "Yes." Responses were then summed to create an ordinal measure of perceived school discrimination, ranging from zero to three, with higher scores indicating greater experiences of discrimination in school.

Box 1. Items of perceived school discrimination

2.2.4. Outcomes

List Sorting Working Memory Task: ABCD has measured working memory using the NIH Toolbox List Sorting Working Memory Task. We used the age-corrected score. The resulting score is a continuous variable, where higher scores indicate better working memory.

Picture Vocabulary Task: ABCD has measured language and cognitive ability (learning) using the NIH Toolbox Picture Vocabulary Task. We used the age-corrected score. This task assesses a participant's ability to name the picture which is shown. The resulting score is a continuous variable, where a higher score indicates better cognitive function, reflecting greater learning and language ability.

NIH Toolbox Oral Reading Recognition Test: Reading ability was assessed using the NIH Toolbox Oral Reading Recognition Test. We used the age-corrected score to account for developmental differences across participants. This test measures a student's ability to recognize, comprehend, and read written words. Like other cognitive scores, the reading ability score is a continuous variable, with higher scores reflecting greater reading proficiency.

School Discipline (Suspension): School disciplinary actions were measured using a self-reported item that asked students whether they had ever been suspended from school. This variable was binary, with responses coded as 1 for students who had been suspended and 0 for those who had not. This measure captures an important aspect of school disciplinary actions often associated with racial disparities and social justice.

Depressive Symptoms (Withdrawal): Depressive symptoms were measured using the depression and withdrawal subscale from the Child Behavior Checklist (CBC). This subscale provides a continuous measure of depressive symptoms, where higher scores indicate greater levels of depression and withdrawal behaviors. The CBC is widely used in research for assessing emotional and behavioral problems in children and adolescents.

2.2.5. Covariates

Several covariates were included to control for other factors that might influence educational outcomes:

Child’s age: Continuous variable to account for developmental differences.

Child’s gender: Dichotomized as male and female.

Parental marital status: Included to account for family structure, which may influence educational experiences and outcomes. This variable was coded as 1 for married and 0 for not married.

2.3. Statistical Analysis

We utilized Structural Equation Modeling (SEM) to examine the effects of race, parental education, and their interaction on perceived school discrimination, and subsequently, how perceived school discrimination influenced educational, cognitive, and emotional outcomes across the five levels of childhood educational opportunity. SEM was chosen for its ability to simultaneously model multiple relationships among variables, making it well-suited for assessing the interaction between race and other factors, such as COI. The primary focus of the analysis was on the coefficient of the interaction between race (coded as Black = 1, White = 0) and parental education, which allowed us to quantify the diminished returns of parental education on perceived school discrimination for Black students compared to their White peers.

We modeled the paths from perceived school discrimination to various outcomes, including educational achievement, cognitive performance, and emotional wellbeing. Additionally, we performed multigroup SEM analyses, where the groups were defined based on the different levels of educational opportunity (COI). This approach enabled us to explore whether the relationship between race, parental education, and school discrimination varied across residential areas s with differing levels of childhood educational opportunity. By conducting these multigroup comparisons, we could determine whether higher educational opportunity levels intensified or mitigated the negative impact of perceived school discrimination on Black students' outcomes.

2.4. Ethical Considerations

The ABCD Study adhered to stringent ethical guidelines and was approved by the institutional review boards (IRBs) of all participating research institutions. Parents or legal guardians provided informed consent for their children's participation, and the children themselves provided assent. To ensure participant privacy and confidentiality, all data were de-identified throughout the research process. These measures ensured compliance with ethical standards and protected the rights and welfare of all participants.

3. Results

Table 1 provides the descriptive statistics for the key study variables. The average age of the children in the sample was 9.0 years (SE = 0.005), with a 95% confidence interval ranging from 9.47 to 9.49. Depression levels, represented as Z-scores, had a mean of -0.014 (SE = 0.010), indicating slightly below-average depression symptoms. The mean level of perceived school discrimination was 1.281 (SE = 0.006), with a confidence interval between 1.268 and 1.293.

Table 1
Descriptive Data Overall

In terms of race, 72.9% of the sample identified as White (SE = 0.006), and 27.1% identified as Black (SE = 0.006). When broken down by educational childhood opportunity index (COI) levels, 17.1% of the children lived in the lowest opportunity areas, 11.8% in low opportunity areas, 15.3% in average opportunity areas, 21.7% in high opportunity areas, and 34.1% in the highest opportunity areas.

The sample was fairly balanced by gender, with 47.6% of participants identifying as female (SE = 0.007) and 52.4% as male (SE = 0.007). Regarding the marital status of the household, 34.0% of children lived in an unwed household (SE = 0.006), while 66.0% lived in a married household (SE = 0.006).

Finally, the majority of children had not been suspended from school, with 93.7% reporting no suspension (SE = 0.003), and 6.3% having experienced suspension (SE = 0.003).

The correlation matrix presented in Table 2 shows significant associations among the key study variables. Being Black (Race) was significantly correlated with lower reading scores (r = -0.211, p < 0.05), list sorting working memory (r = -0.23, p < 0.05), and picture Vocabulary (r = -0.33, p < 0.05). Black children were also significantly more likely to experience school suspension (r = 0.215, p < 0.05) and report higher levels of perceived school discrimination (r = 0.167, p < 0.05). Age was not significantly correlated with race (r = -0.008, p > 0.05), but was positively associated with a higher likelihood of school suspension (r = 0.042, p < 0.05). Male children were more likely to face school suspension (r = 0.133, p < 0.05) and perceive higher school discrimination (r = 0.090, p < 0.05). Living in a married household was associated with better cognitive function (r = 0.094, p < 0.05), higher reading scores (r = 0.206, p < 0.05), and lower rates of both perceived school discrimination (r = -0.117, p < 0.05) and school suspension (r = -0.183, p < 0.05). Depression was not significantly associated with race (r = 0.038, p < 0.05), but was positively correlated with school suspension (r = 0.130, p < 0.05) and school discrimination (r = 0.078, p < 0.05).

Table 2
Pearson Correlation between Study Variables

Table 3 presents a summary of the multi-group Structural Equation Models (SEMs) across groups defined by different levels of educational childhood opportunity index (COI). Figure 1-1 to 1-5 show the models. Our findings showed that Black-White disparities to the disadvantage of high discrimination of high SES Black children can be seen in areas with highest COIs. This is based on the observation that interaction between race and parental education on experiences of discrimination were only significant in highest-opportunity areas. Then, across areas with different COI levels, Black students experienced a disproportionately higher school discrimination had higher suspension, worse depression, and worse cognitive performance.

Table 3
Summary of structural equation model (SEM) across educational COI levels
Figure 1
Race by parental education effects on students’ experiences of discrimination and educational, cognitive, and emotional outcomes

4. Discussion

This study sets out to examine the effects of race, parental education, and educational opportunity on perceived school discrimination and subsequent educational and emotional outcomes. We hypothesized that while higher levels of educational COI would generally be associated with improved outcomes, Black students—particularly those from high-SES backgrounds—would experience increased discrimination in these high-opportunity environments, thereby limiting the benefits of their SES.

The first key takeaway from our analysis is that higher parental education is associated with lower perceived school discrimination overall. This finding aligns with prior research suggesting that higher SES, reflected through parental education, generally reduces the perception of discrimination among children, youth, and adults. More educated parents tend to have greater social capital, better knowledge of how to navigate institutional systems, and the ability to advocate for their children more effectively. These factors can shield their children from certain forms of discrimination, at least in typical school environments. For the general population, higher parental education and SES are typically protective factors that buffer against the negative effects of discrimination.

However, a more concerning and nuanced finding from our study is that, in areas with the highest COI, high-SES Black students report significantly higher levels of perceived discrimination compared to their White peers. This suggests that in the most advantaged educational settings—where resources, school quality, and opportunities for academic success are highest—Black students continue to face disproportionately high levels of unfair treatment by teachers and school staff. These findings challenge the assumption that improving access to high-quality educational environments will automatically close racial gaps in school experiences and outcomes.

Our results align with the Marginalization-Related Diminished Returns (MDRs) framework, which posits that Black individuals, despite having access to higher SES resources (such as education or income), often experience fewer positive outcomes from these resources due to systemic discrimination and bias. In this context, even though Black students in high-COI areas theoretically have greater opportunities for success, their experiences of heightened racial bias may negate or even reverse the expected benefits of these educational environments. Discrimination can lead to lower academic engagement, reduced sense of belonging, and decreased emotional wellbeing, all of which negatively impact academic outcomes. Thus, rather than benefiting equally from their high SES, Black students may be placed at a unique disadvantage in these high-opportunity environments due to the persistence of racial bias.

The finding that higher COI is associated with increased experiences of school discrimination and suspension rates for Black students highlights an important challenge for policymakers and educators striving for educational equity. It suggests that simply improving the overall quality of educational opportunities is insufficient to address the unique barriers faced by Black students, especially those from higher SES backgrounds. Without tackling the underlying racial biases present in schools, high-COI environments may unintentionally perpetuate or exacerbate racial disparities.

Moreover, our results point to the critical need for systemic interventions that address the roots of school-based discrimination. Anti-racist training for educators, administrators, and school staff is essential for raising awareness of implicit biases and discriminatory behaviors that may disproportionately affect Black students. Reforms in school disciplinary policies, such as adopting restorative justice approaches rather than punitive measures like suspension, are necessary to reduce racial disparities in discipline. Additionally, increasing accountability for discriminatory practices within schools can help create a more equitable environment where all students, regardless of race, can thrive.

These results are also indicative of "Minority Diminished Returns" (MDRs) [65, 66, 67, 68, 69]. Diminished returns of family are supported by evidence showing that Black children often do not benefit from socioeconomic resources to the same extent as their White counterparts. Despite achieving similar levels of parental education and income, Black families frequently face structural barriers such as residential segregation, discrimination in housing and employment, and underfunded schools in predominantly Black neighborhoods [27, 28, 70, 71, 72, 73, 74, 75]. These systemic inequalities reduce the impact of family SES on educational opportunities. For example, research has shown that in affluent neighborhoods, Black families encounter discrimination and isolation [50, 55, 76]. Additionally, systemic discrimination in school systems, including disparities in disciplinary practices and tracking, further limits Black children's access to the full range of educational opportunities, undermining the potential benefits of parental education and income [77]. These structural factors contribute to the weaker association between family SES and educational outcomes for Black children, highlighting the need for policies that address racial inequities at multiple levels, from housing to school funding.

In addition to diminished educational opportunities, our findings may explain why we observe weaker developmental benefits typically associated with higher SES for Black than White children [78]. This aligns with previous research showing that Black children from high SES backgrounds often exhibit weaker brain development outcomes compared to their White peers [79, 80, 81, 82, 83]. Factors such as chronic stress, exposure to trauma, and limited access to mental health resources may contribute to this discrepancy, reducing the impact of parental education and income on Black children’s brain development.

4.1. Limitations

Despite the robust dataset from the ABCD study and the advanced modeling techniques used, this research has several limitations. First, the cross-sectional nature of the data limits our ability to establish causal relationships between COI and racial disparities in educational outcomes. Longitudinal data would provide a clearer picture of how these disparities evolve over time and whether changes in educational opportunity or school policies influence the observed outcomes. Second, our reliance on COI rankings as a measure of educational opportunity may oversimplify the complex factors that contribute to school quality and student success. Future research could incorporate more nuanced measures of school environments, including teacher quality, curriculum diversity, and peer support. Lastly, the study does not account for potential variation in individual student experiences within the same areas, which may be influenced by factors such as socioeconomic status, neighborhood segregation, or parental involvement.

4.2. Next Research Steps

Future research should aim to build on these findings by addressing the limitations mentioned above. Longitudinal studies that track students over time could offer deeper insights into the causal relationships between educational opportunities, racial disparities, and student outcomes. Additionally, future studies should explore the intersection of race with other variables such as gender, immigration status, and socioeconomic background to understand how different forms of marginalization interact with educational opportunities and bias. Researchers should also examine specific school policies and practices—such as zero-tolerance discipline policies and school-level anti-racism initiatives—that may influence racial disparities in disciplinary actions and discrimination. Finally, future work could investigate interventions designed to reduce school-based discrimination and disciplinary disparities, assessing their effectiveness in reducing the racial gap in both academic achievement and experiences of unfair treatment. By expanding our understanding of these dynamics, future research can contribute to more comprehensive strategies for promoting racial equity in education.

4.3. Implications

Our study also has important implications for future research. While we focused on the interaction between race, parental education, and educational opportunity, future work should explore other factors that may influence the experiences of Black students in high-COI residential areas, such as neighborhood racial composition, peer dynamics, and teacher-student relationships. Additionally, longitudinal research is needed to examine how these experiences of discrimination affect long-term outcomes, including college enrollment, career success, and mental health. Addressing these gaps in the literature will provide a more comprehensive understanding of how racial disparities in educational experiences and outcomes can be effectively mitigated.

5. Conclusion

In conclusion, this study underscores the complexity of addressing racial disparities in education. While improving educational opportunities is critical, it must be accompanied by targeted efforts to reduce school-based discrimination. Creating equitable educational environments where Black students can fully benefit from their socioeconomic resources requires both structural reforms and a commitment to challenging and dismantling the racial biases that persist within schools.

Author Contributions: 

Conceptualization, SA; methodology SA; validation HZ; formal analysis, SA.; resources, SA and HZ; data curation, SA; writing—original draft preparation, SA; writing—review and editing, HZ visualization, SA; supervision HZ, project administration, SA; All authors have read and agreed to the published version of the manuscript.

Authors’ Funding:

Part of Hossein Zare effort comes from the NIMHD U54MD000214. Shervin Assari is supported by funds provided by The Regents of the University of California, Tobacco-Related Diseases Research Program, Grant Number no T32IR5355.

ABCD Funding: 

Data used in the preparation of this article were obtained from the Adolescent Brain Cognitive Development (ABCD) Study (https://abcdstudy.org), held in the NIMH Data Archive (NDA). This is a multisite, longitudinal study designed to recruit more than 10,000 children age 9–10 and follow them over 10 years into early adulthood. The opinions, findings, and conclusions herein are those of the authors and not necessarily represent The Regents of the University of California, or any of its programs. The ABCD Study® is supported by the National Institutes of Health and additional federal partners under award numbers U01DA041048, U01DA050989, U01DA051016, U01DA041022, U01DA051018, U01DA051037, U01DA050987, U01DA041174, U01DA041106, U01DA041117, U01DA041028, U01DA041134, U01DA050988, U01DA051039, U01DA041156, U01DA041025, U01DA041120, U01DA051038, U01DA041148, U01DA041093, U01DA041089, U24DA041123, U24DA041147. A full list of supporters is available at https://abcdstudy.org/federal-partners.html. A listing of participating sites and a complete listing of the study investigators can be found at https://abcdstudy.org/consortium_members/. ABCD consortium investigators designed and implemented the study and/or provided data but did not necessarily participate in the analysis or writing of this report. This manuscript reflects the views of the authors and may not reflect the opinions or views of the NIH or ABCD consortium investigators.

References

  1. Anderson E. Reflections on the “Black-white Achievement Gap”. J Sch Psychol. Oct 2012;50(5):593-7. doi:10.1016/j.jsp.2012.08.007[CrossRef] [PubMed]
  2. Yeung WJ. Explaining the Black–White achievement gap: An intergenerational stratification and developmental perspective. 2012;[CrossRef]
  3. Braun H, Chapman L, Vezzu S. The black-white achievement gap revisited. education policy analysis archives. 2010;18:21.[CrossRef]
  4. Burchinal M, McCartney K, Steinberg L, et al. Examining the Black-White achievement gap among low-income children using the NICHD study of early child care and youth development. Child Dev. Sep-Oct 2011;82(5):1404-20. doi:10.1111/j.1467-8624.2011.01620.x[CrossRef] [PubMed]
  5. Cricci BD. Racial gaps in intergenerational mobility and school factors: evidence from the State of São Paulo. Universidade de São Paulo; 2023.
  6. Farkas G. The black-white test score gap. Contexts. 2004;3(2):12-19.[CrossRef]
  7. Fryer Jr RG, Levitt SD. The black-white test score gap through third grade. American law and economics review. 2006;8(2):249-281.[CrossRef]
  8. Hartney MT, Flavin P. The political foundations of the Black–White education achievement gap. American Politics Research. 2014;42(1):3-33.[CrossRef]
  9. Hamilton D, Darity Jr W. Race, Wealth, and Intergenerational Poverty: There will never be a post-racial America if the wealth gap persists. The American Prospect. 2009;20(7):A10-A12.
  10. Health WCoSDo, Organization WH. Closing the gap in a generation: health equity through action on the social determinants of health: Commission on Social Determinants of Health final report. World Health Organization; 2008.
  11. Hemphill FC, Vanneman A. Achievement Gaps: How Hispanic and White Students in Public Schools Perform in Mathematics and Reading on the National Assessment of Educational Progress. Statistical Analysis Report. NCES 2011-459. National Center for Education Statistics. 2011;
  12. Herring C, Henderson L. Wealth Inequality in Black and White: Cultural and Structural Sources of the Racial Wealth Gap. Race and Social Problems. 2016/03/01 2016;8(1):4-17. doi:10.1007/s12552-016-9159-8[CrossRef]
  13. Berlak H. Race and the achievement gap. Rethinking schools. 2001;15(4):10-11.
  14. Paige R, Witty E. The black-white achievement gap. Amacom; 2010.
  15. Lee J. Racial and ethnic achievement gap trends: Reversing the progress toward equity? Educational researcher. 2002;31(1):3-12.[CrossRef]
  16. Adelman RM. Neighborhood opportunities, race, and class: The Black middle class and residential segregation. City & Community. 2004;3(1):43-63.[CrossRef]
  17. Card D, Rothstein J. Racial segregation and the black–white test score gap. Journal of Public Economics. 2007;91(11-12):2158-2184.[CrossRef]
  18. Pattillo M. Black middle-class neighborhoods. Annu Rev Sociol. 2005;31(1):305-329.[CrossRef]
  19. Orfield G, Jarvie D. Black segregation matters: School resegregation and Black educational opportunity. 2020;
  20. Lesson J. A STATISTICAL SUMMARY, STATE BY STATE, OF SCHOOL SEGREGATION-DESEGREGATION IN THE SOUTHERN AND BORDER AREA FROM 1954 TO THE PRESENT. 1964;
  21. Moody J. Race, school integration, and friendship segregation in America. American journal of Sociology. 2001;107(3):679-716.[CrossRef]
  22. Owens A. Income segregation between school districts and inequality in students’ achievement. Sociology of education. 2018;91(1):1-27.[CrossRef]
  23. Walsh C. Racial taxation: Schools, segregation, and taxpayer citizenship, 1869–1973. UNC Press Books; 2018.[CrossRef]
  24. Albrecht CM, Albrecht DE. Social status, adolescent behavior, and educational attainment. Sociological spectrum. 2010;31(1):114-137.[CrossRef]
  25. Tynkkynen L, Vuori J, Salmela-Aro K. The role of psychological control, socioeconomic status and academic achievement in parents' educational aspirations for their adolescent children. European Journal of Developmental Psychology. 2012;9(6):695-710.[CrossRef]
  26. Suna HE, Tanberkan H, Gür B, Perc M, Özer M. Socioeconomic status and school type as predictors of academic achievement. Journal of Economy Culture and Society. 2020;(61):41-64.
  27. Gee GC, Ford CL. Structural racism and health inequities: Old issues, New Directions1. Du Bois review: social science research on race. 2011;8(1):115-132.[CrossRef] [PubMed]
  28. Gee GC, Hicken MT. Structural racism: the rules and relations of inequity. Ethnicity & Disease. 2021;31(Suppl 1):293.[CrossRef] [PubMed]
  29. Halliwell HA, Kirksey B, Cheldy Martinez B, Micharri Pratts B. “It‟ s Like the Elephant in the Room”: A Qualitative Analysis of Racism in a US High School. World. 2022;9(4)[CrossRef]
  30. McKenzie K. Racism and health: Antiracism is an important health issue. British Medical Journal Publishing Group; 2003. p. 65-66.[CrossRef] [PubMed]
  31. Piper ME, Maddox R, Castro Y, et al. Lessons learned on addressing racism: recommendations from the Society for Research on Nicotine and Tobacco’s Racial Equity Task Force. Addiction (Abingdon, England). 2022;117(10):2567.[CrossRef] [PubMed]
  32. Wilson S. Racism Is Real. Racism Is Complicated. Racism Is Real Complicated. Family Medicine. 2019;51(1):8-10.[CrossRef] [PubMed]
  33. Zarate MA. Racism in the 21st century. Handbook of prejudice, stereotyping, and discrimination. 2009:387-406.
  34. Herrnstein RJ, Murray CA. The bell curve: Intelligence and class structure in American life. The bell curve: Intelligence and class structure in American life. Free Press; 1994:xxvi, 845-xxvi, 845.
  35. Dobbie W, Fryer RG. Are high quality schools enough to close the achievement gap? Evidence from a social experiment in Harlem. 2009.[CrossRef]
  36. Hung M, Smith WA, Voss MW, Franklin JD, Gu Y, Bounsanga J. Exploring student achievement gaps in school districts across the United States. Education and Urban Society. 2020;52(2):175-193.[CrossRef]
  37. Murnane RJ, Willett JB, Bub KL, McCartney K, Hanushek E, Maynard R. Understanding trends in the black-white achievement gaps during the first years of school [with comments]. Brookings-Wharton papers on urban affairs. 2006:97-135.[CrossRef]
  38. Phillips M, Crouse J, Ralph J. Does the black–white test score gap widen after children enter school? 1998;
  39. Rothbart MW. Does school finance reform reduce the race gap in school funding? Education Finance and Policy. 2020;15(4):675-707.[CrossRef]
  40. Talbert-Johnson C. Structural inequities and the achievement gap in urban schools. Education and Urban Society. 2004;37(1):22-36.[CrossRef]
  41. Luthar SS. The culture of affluence: Psychological costs of material wealth. Child development. Nov-Dec 2003;74(6):1581-1593. doi:10.1046/j.1467-8624.2003.00625.x[CrossRef] [PubMed]
  42. Luthar SS, Becker BE. Privileged but pressured? A study of affluent youth. Child development. 2002;73(5):1593-1610.[CrossRef] [PubMed]
  43. Luthar SS, Kumar NL, Zillmer N. High-Achieving Schools Connote Risks for Adolescents: Problems Documented, Processes Implicated, and Directions for Interventions. Am Psychol. Oct 2019;75(7):983-995. doi:10.1037/amp0000556[CrossRef] [PubMed]
  44. Assari S, Caldwell CH. High Risk of Depression in High-Income African American Boys. J Racial Ethn Health Disparities. Aug 2018;5(4):808-819. doi:10.1007/s40615-017-0426-1[CrossRef] [PubMed]
  45. Luthar SS, Barkin SH, Crossman EJ. “I can, therefore I must”: Fragility in the upper-middle classes. Development and Psychopathology. 2013;25(4 0 2):1529.[CrossRef] [PubMed]
  46. Luthar SS, D'AVANZO K. Contextual factors in substance use: A study of suburban and inner-city adolescents. Development and Psychopathology. 1999;11(4):845-867.[CrossRef] [PubMed]
  47. Luthar SS, Sexton CC. The high price of affluence. Advances in child development and behavior. Elsevier; 2004:125-162.[CrossRef] [PubMed]
  48. Luthar SS, Small PJ, Ciciolla L. Adolescents from upper middle class communities: Substance misuse and addiction across early adulthood. Development and psychopathology. 2018;30(1):315-335.[CrossRef] [PubMed]
  49. McMahon TJ, Luthar SS. Patterns and correlates of substance use among affluent, suburban high school students. Journal of Clinical Child and Adolescent Psychology. 2006;35(1):72-89.[CrossRef] [PubMed]
  50. Assari S. Does school racial composition explain why high income black youth perceive more discrimination? A gender analysis. Brain sciences. 2018;8(8):140.[CrossRef] [PubMed]
  51. Assari S. Social Epidemiology of Perceived Discrimination in the United States: Role of Race, Educational Attainment, and Income. Int J Epidemiol Res. Summer 2020;7(3):136-141. doi:10.34172/ijer.2020.24[CrossRef] [PubMed]
  52. Assari S, Caldwell CH. Teacher Discrimination Reduces School Performance of African American Youth: Role of Gender. Brain Sci. Sep 30 2018;8(10)doi:10.3390/brainsci8100183[CrossRef] [PubMed]
  53. Assari S, Cochran SD, Mays VM. Money Protects White but Not African American Men against Discrimination: Comparison of African American and White Men in the Same Geographic Areas. Int J Environ Res Public Health. Mar 8 2021;18(5)doi:10.3390/ijerph18052706[CrossRef] [PubMed]
  54. Assari S, Gibbons FX, Simons RL. Perceived Discrimination among Black Youth: An 18-Year Longitudinal Study. Behav Sci (Basel). Apr 27 2018;8(5)doi:10.3390/bs8050044[CrossRef] [PubMed]
  55. Assari S, Moghani Lankarani M. Workplace racial composition explains high perceived discrimination of high socioeconomic status African American men. Brain sciences. 2018;8(8):139.[CrossRef] [PubMed]
  56. Assari S, Preiser B, Lankarani MM, Caldwell CH. Subjective Socioeconomic Status Moderates the Association between Discrimination and Depression in African American Youth. Brain Sci. Apr 20 2018;8(4)doi:10.3390/brainsci8040071[CrossRef] [PubMed]
  57. Assari S, Zare H. Black-White Differences in The Effects of Parental Education on College Students’ Beliefs about Racial Discrimination. Open Journal of Educational Research. 07/31 2024;4(4):164-173.[CrossRef] [PubMed]
  58. Rodriguez JM, Koo C, Di Pasquale G, Assari S. Black-White differences in perceived lifetime discrimination by education and income in the MIDUS Study in the U.S. J Biosoc Sci. Sep 2023;55(5):795-811. doi:10.1017/s0021932022000360[CrossRef] [PubMed]
  59. Assari S, Boyce S, Caldwell CH, Bazargan M. Parental Educational Attainment and Black-White Adolescents' Achievement Gap: Blacks' Diminished Returns. Open J Soc Sci. Mar 2020;8(3):282-297. doi:10.4236/jss.2020.83026[CrossRef] [PubMed]
  60. Assari S, Mardani A, Maleki M, Boyce S, Bazargan M. Black-White Achievement Gap: Role of Race, School Urbanity, and Parental Education. Pediatric Health Med Ther. 2021;12:1-11. doi:10.2147/PHMT.S238877[CrossRef] [PubMed]
  61. Shervin Assari CHC, Mohsen Bazargan. Parental Educational Attainment and Black-White Adolescents’ Achievement Gap: Blacks’ Diminished Returns. Open Journal of Social Sciences. Mar 2020;8(3):282-297. doi:10.4236/jss.2020.83026[CrossRef] [PubMed]
  62. Assari S. Health disparities due to diminished return among black Americans: Public policy solutions. Social Issues and Policy Review. 2018;12(1):112-145.[CrossRef]
  63. Assari S. Unequal gain of equal resources across racial groups. International journal of health policy and management. 2018;7(1):1.[CrossRef] [PubMed]
  64. Jaeger DA. Reconciling the old and new census bureau education questions: Recommendations for researchers. Journal of Business & Economic Statistics. 1997;15(3):300-309.[CrossRef]
  65. Assari S, Zare H. Unequal Effect of Educational Attainment on Reducing Poverty and Welfare; Diminished Returns of American Indian/Alaska Native Populations. J Rehabil Ther. 2024;6(2):1-11. doi:10.29245/2767-5122/2024/2.1143[CrossRef]
  66. Assari SA, G., Boyce, S., Bazargan, M., Caldwell, C.,. Parental Human Capital and Adolescents’ Executive Function: Immigrants’ Diminished Returns. . Medical Research Archives. 2020;8(10):1-20. doi:10.18103/mra.v8i10.2235[CrossRef] [PubMed]
  67. Bakhtiari E. Diminished returns in Europe: socioeconomic status and ethno-racial health disparities across 30 countries in the European social survey. Journal of Racial and Ethnic Health Disparities. 2022;9(6):2412-2426.[CrossRef] [PubMed]
  68. S A. Minorities Diminished Returns. MedLine Publications. 2020;
  69. Shervin A. Parental Education and Spanking of American Children: Blacks’ Diminished Returns. World journal of educational research (Los Angeles, Calif). 2020;8(2)
  70. Gee GC, Ford CL. STRUCTURAL RACISM AND HEALTH INEQUITIES: Old Issues, New Directions. Du Bois Rev. Apr 2011;8(1):115-132. doi:10.1017/S1742058X11000130[CrossRef] [PubMed]
  71. Gee GC, Hing A, Mohammed S, Tabor DC, Williams DR. Racism and the Life Course: Taking Time Seriously. Am J Public Health. Jan 2019;109(S1):S43-s47. doi:10.2105/ajph.2018.304766[CrossRef] [PubMed]
  72. Gee GC, Walsemann KM, Brondolo E. A life course perspective on how racism may be related to health inequities. Am J Public Health. May 2012;102(5):967-74. doi:10.2105/AJPH.2012.300666[CrossRef] [PubMed]
  73. Paradies Y, Ben J, Denson N, et al. Racism as a Determinant of Health: A Systematic Review and Meta-Analysis. PLoS One. 2015;10(9):e0138511. doi:10.1371/journal.pone.0138511[CrossRef] [PubMed]
  74. Paradies Y, Priest N, Ben J, et al. Racism as a determinant of health: a protocol for conducting a systematic review and meta-analysis. Syst Rev. Sep 23 2013;2:85. doi:10.1186/2046-4053-2-85[CrossRef] [PubMed]
  75. Shariff-Marco S, Breen N, Landrine H, et al. MEASURING EVERYDAY RACIAL/ETHNIC DISCRIMINATION IN HEALTH SURVEYS: How Best to Ask the Questions, in One or Two Stages, Across Multiple Racial/Ethnic Groups? Du Bois Rev. Spring 2011;8(1):159-177. doi:10.1017/S1742058X11000129[CrossRef] [PubMed]
  76. Assari S, Gibbons FX, Simons RL. Perceived discrimination among black youth: An 18-year longitudinal study. Behavioral sciences. 2018;8(5):44.[CrossRef] [PubMed]
  77. Monroe CR. Why are" bad boys" always black?: Causes of disproportionality in school discipline and recommendations for change. The Clearing House: A Journal of Educational Strategies, Issues and Ideas. 2005;79(1):45-50.[CrossRef]
  78. Assari S, Akhlaghipour G, Boyce S, Bazargan M, Caldwell CH. Parental Human Capital and Adolescents’ Executive Function: Immigrants’ Diminished Returns. Medical research archives. 2020;8(10)[CrossRef] [PubMed]
  79. Assari S. Dimensional Change Card Sorting of American Children: Marginalization-Related Diminished Returns of Age. Child Teenagers. 2020;3(2):72-92. doi:10.22158/ct.v3n2p72[CrossRef] [PubMed]
  80. Assari S. Age-Related Decline in Children's Reward Sensitivity: Blacks' Diminished Returns. Res Health Sci. 2020;5(3):112-128. doi:10.22158/rhs.v5n3p112[CrossRef] [PubMed]
  81. Assari S. Parental Education and Nucleus Accumbens Response to Reward Anticipation: Minorities' Diminished Returns. Adv Soc Sci Cult. 2020;2(4):132-153. doi:10.22158/assc.v2n4p132[CrossRef] [PubMed]
  82. Assari S. Mental Rotation in American Children: Diminished Returns of Parental Education in Black Families. Pediatr Rep. Nov 20 2020;12(3):130-141. doi:10.3390/pediatric12030028[CrossRef] [PubMed]
  83. Assari S, Boyce S. Family's Subjective Economic Status and Children's Matrix Reasoning: Blacks' Diminished Returns. Res Health Sci. Nov 29 2021;6(1):1-23. doi:10.22158/rhs.v6n1p1[CrossRef] [PubMed]
Article metrics
Views
445
Downloads
158

Cite This Article

APA Style
Assari, S. , & Zare, H. (2024). The Cost of Opportunity: Anti-Black Discrimination in High Resource Settings. Journal of Biomedical and Life Sciences, 4(2), 92-110. https://doi.org/10.31586/jbls.2024.1128
ACS Style
Assari, S. ; Zare, H. The Cost of Opportunity: Anti-Black Discrimination in High Resource Settings. Journal of Biomedical and Life Sciences 2024 4(2), 92-110. https://doi.org/10.31586/jbls.2024.1128
Chicago/Turabian Style
Assari, Shervin, and Hossein Zare. 2024. "The Cost of Opportunity: Anti-Black Discrimination in High Resource Settings". Journal of Biomedical and Life Sciences 4, no. 2: 92-110. https://doi.org/10.31586/jbls.2024.1128
AMA Style
Assari S, Zare H. The Cost of Opportunity: Anti-Black Discrimination in High Resource Settings. Journal of Biomedical and Life Sciences. 2024; 4(2):92-110. https://doi.org/10.31586/jbls.2024.1128 
@Article{jbls1128,
AUTHOR = {Assari, Shervin and Zare, Hossein},
TITLE = {The Cost of Opportunity: Anti-Black Discrimination in High Resource Settings},
JOURNAL = {Journal of Biomedical and Life Sciences},
VOLUME = {4},
YEAR = {2024},
NUMBER = {2},
PAGES = {92-110},
URL = {https://www.scipublications.com/journal/index.php/JBLS/article/view/1128},
ISSN = {2771-2303},
DOI = {10.31586/jbls.2024.1128},
ABSTRACT = {Objective: Inequalities exist in children’s educational outcomes—including reading proficiency, school discrimination, and school disciplinary actions—across zip codes with different levels of educational childhood opportunity index (COI). This study examines the interaction between race and educational environment on children’s educational outcomes. We hypothesize that race, parental education, and their interaction are associated with perceived school discrimination, which in turn reduces their cognitive, academic, and emotional wellbeing. We also hypothesize that Black children with high socioeconomic status (SES) report high perceived school discrimination in high-COI settings. Methods: Data were drawn from the Adolescent Brain Cognitive Development (ABCD) study, which measures a wide range of educational, cognitive, and emotional outcomes. At the same time, the ABCD children are sampled across areas with vast differences in COI rankings, that can be classified into these five categories: very high, high, average, low, and very low educational COIs. Our structural equation models (SEM) tested the additive and interactive effects of race and educational attainment on perceived school discrimination, and the effects of school discrimination on various cognitive abilities (reading proficiency, picture vocabulary, and list sorting working memory), school suspension, as well as depressed mood. Our multi-group SEM assessed how these relationships vary across educational COI levels. Results: Our findings showed that high SES Black children report highest school discrimination in residential areas with highest COIs. This is based on the observation that the interaction between race and parental education on experiences of school discrimination were only significant in areas with highest COI. Across residential areas with different COI levels, students who experienced higher school discrimination had higher suspension, worse depression, and worse cognitive performance. Conclusion: While higher COIs are associated with better academic outcomes, Black-White gaps exist in the role of increased COI through increased racial bias that children perceive. These findings underscore the complexity of educational equity, suggesting that improving COI alone is insufficient for eliminating racial disparities in school experiences. Policies should be in place to reduce school-based discrimination against Black students in high COI settings.},
}
%0 Journal Article
%A Assari, Shervin
%A Zare, Hossein
%D 2024
%J Journal of Biomedical and Life Sciences

%@ 2771-2303
%V 4
%N 2
%P 92-110

%T The Cost of Opportunity: Anti-Black Discrimination in High Resource Settings
%M doi:10.31586/jbls.2024.1128
%U https://www.scipublications.com/journal/index.php/JBLS/article/view/1128

TY  - JOUR
AU  - Assari, Shervin
AU  - Zare, Hossein
TI  - The Cost of Opportunity: Anti-Black Discrimination in High Resource Settings
T2  - Journal of Biomedical and Life Sciences
PY  - 2024
VL  - 4
IS  - 2
SN  - 2771-2303
SP  - 92
EP  - 110
UR  - https://www.scipublications.com/journal/index.php/JBLS/article/view/1128
AB  - Objective: Inequalities exist in children’s educational outcomes—including reading proficiency, school discrimination, and school disciplinary actions—across zip codes with different levels of educational childhood opportunity index (COI). This study examines the interaction between race and educational environment on children’s educational outcomes. We hypothesize that race, parental education, and their interaction are associated with perceived school discrimination, which in turn reduces their cognitive, academic, and emotional wellbeing. We also hypothesize that Black children with high socioeconomic status (SES) report high perceived school discrimination in high-COI settings. Methods: Data were drawn from the Adolescent Brain Cognitive Development (ABCD) study, which measures a wide range of educational, cognitive, and emotional outcomes. At the same time, the ABCD children are sampled across areas with vast differences in COI rankings, that can be classified into these five categories: very high, high, average, low, and very low educational COIs. Our structural equation models (SEM) tested the additive and interactive effects of race and educational attainment on perceived school discrimination, and the effects of school discrimination on various cognitive abilities (reading proficiency, picture vocabulary, and list sorting working memory), school suspension, as well as depressed mood. Our multi-group SEM assessed how these relationships vary across educational COI levels. Results: Our findings showed that high SES Black children report highest school discrimination in residential areas with highest COIs. This is based on the observation that the interaction between race and parental education on experiences of school discrimination were only significant in areas with highest COI. Across residential areas with different COI levels, students who experienced higher school discrimination had higher suspension, worse depression, and worse cognitive performance. Conclusion: While higher COIs are associated with better academic outcomes, Black-White gaps exist in the role of increased COI through increased racial bias that children perceive. These findings underscore the complexity of educational equity, suggesting that improving COI alone is insufficient for eliminating racial disparities in school experiences. Policies should be in place to reduce school-based discrimination against Black students in high COI settings.
DO  - The Cost of Opportunity: Anti-Black Discrimination in High Resource Settings
TI  - 10.31586/jbls.2024.1128
ER  -
  1. Anderson E. Reflections on the “Black-white Achievement Gap”. J Sch Psychol. Oct 2012;50(5):593-7. doi:10.1016/j.jsp.2012.08.007[CrossRef] [PubMed]
  2. Yeung WJ. Explaining the Black–White achievement gap: An intergenerational stratification and developmental perspective. 2012;[CrossRef]
  3. Braun H, Chapman L, Vezzu S. The black-white achievement gap revisited. education policy analysis archives. 2010;18:21.[CrossRef]
  4. Burchinal M, McCartney K, Steinberg L, et al. Examining the Black-White achievement gap among low-income children using the NICHD study of early child care and youth development. Child Dev. Sep-Oct 2011;82(5):1404-20. doi:10.1111/j.1467-8624.2011.01620.x[CrossRef] [PubMed]
  5. Cricci BD. Racial gaps in intergenerational mobility and school factors: evidence from the State of São Paulo. Universidade de São Paulo; 2023.
  6. Farkas G. The black-white test score gap. Contexts. 2004;3(2):12-19.[CrossRef]
  7. Fryer Jr RG, Levitt SD. The black-white test score gap through third grade. American law and economics review. 2006;8(2):249-281.[CrossRef]
  8. Hartney MT, Flavin P. The political foundations of the Black–White education achievement gap. American Politics Research. 2014;42(1):3-33.[CrossRef]
  9. Hamilton D, Darity Jr W. Race, Wealth, and Intergenerational Poverty: There will never be a post-racial America if the wealth gap persists. The American Prospect. 2009;20(7):A10-A12.
  10. Health WCoSDo, Organization WH. Closing the gap in a generation: health equity through action on the social determinants of health: Commission on Social Determinants of Health final report. World Health Organization; 2008.
  11. Hemphill FC, Vanneman A. Achievement Gaps: How Hispanic and White Students in Public Schools Perform in Mathematics and Reading on the National Assessment of Educational Progress. Statistical Analysis Report. NCES 2011-459. National Center for Education Statistics. 2011;
  12. Herring C, Henderson L. Wealth Inequality in Black and White: Cultural and Structural Sources of the Racial Wealth Gap. Race and Social Problems. 2016/03/01 2016;8(1):4-17. doi:10.1007/s12552-016-9159-8[CrossRef]
  13. Berlak H. Race and the achievement gap. Rethinking schools. 2001;15(4):10-11.
  14. Paige R, Witty E. The black-white achievement gap. Amacom; 2010.
  15. Lee J. Racial and ethnic achievement gap trends: Reversing the progress toward equity? Educational researcher. 2002;31(1):3-12.[CrossRef]
  16. Adelman RM. Neighborhood opportunities, race, and class: The Black middle class and residential segregation. City & Community. 2004;3(1):43-63.[CrossRef]
  17. Card D, Rothstein J. Racial segregation and the black–white test score gap. Journal of Public Economics. 2007;91(11-12):2158-2184.[CrossRef]
  18. Pattillo M. Black middle-class neighborhoods. Annu Rev Sociol. 2005;31(1):305-329.[CrossRef]
  19. Orfield G, Jarvie D. Black segregation matters: School resegregation and Black educational opportunity. 2020;
  20. Lesson J. A STATISTICAL SUMMARY, STATE BY STATE, OF SCHOOL SEGREGATION-DESEGREGATION IN THE SOUTHERN AND BORDER AREA FROM 1954 TO THE PRESENT. 1964;
  21. Moody J. Race, school integration, and friendship segregation in America. American journal of Sociology. 2001;107(3):679-716.[CrossRef]
  22. Owens A. Income segregation between school districts and inequality in students’ achievement. Sociology of education. 2018;91(1):1-27.[CrossRef]
  23. Walsh C. Racial taxation: Schools, segregation, and taxpayer citizenship, 1869–1973. UNC Press Books; 2018.[CrossRef]
  24. Albrecht CM, Albrecht DE. Social status, adolescent behavior, and educational attainment. Sociological spectrum. 2010;31(1):114-137.[CrossRef]
  25. Tynkkynen L, Vuori J, Salmela-Aro K. The role of psychological control, socioeconomic status and academic achievement in parents' educational aspirations for their adolescent children. European Journal of Developmental Psychology. 2012;9(6):695-710.[CrossRef]
  26. Suna HE, Tanberkan H, Gür B, Perc M, Özer M. Socioeconomic status and school type as predictors of academic achievement. Journal of Economy Culture and Society. 2020;(61):41-64.
  27. Gee GC, Ford CL. Structural racism and health inequities: Old issues, New Directions1. Du Bois review: social science research on race. 2011;8(1):115-132.[CrossRef] [PubMed]
  28. Gee GC, Hicken MT. Structural racism: the rules and relations of inequity. Ethnicity & Disease. 2021;31(Suppl 1):293.[CrossRef] [PubMed]
  29. Halliwell HA, Kirksey B, Cheldy Martinez B, Micharri Pratts B. “It‟ s Like the Elephant in the Room”: A Qualitative Analysis of Racism in a US High School. World. 2022;9(4)[CrossRef]
  30. McKenzie K. Racism and health: Antiracism is an important health issue. British Medical Journal Publishing Group; 2003. p. 65-66.[CrossRef] [PubMed]
  31. Piper ME, Maddox R, Castro Y, et al. Lessons learned on addressing racism: recommendations from the Society for Research on Nicotine and Tobacco’s Racial Equity Task Force. Addiction (Abingdon, England). 2022;117(10):2567.[CrossRef] [PubMed]
  32. Wilson S. Racism Is Real. Racism Is Complicated. Racism Is Real Complicated. Family Medicine. 2019;51(1):8-10.[CrossRef] [PubMed]
  33. Zarate MA. Racism in the 21st century. Handbook of prejudice, stereotyping, and discrimination. 2009:387-406.
  34. Herrnstein RJ, Murray CA. The bell curve: Intelligence and class structure in American life. The bell curve: Intelligence and class structure in American life. Free Press; 1994:xxvi, 845-xxvi, 845.
  35. Dobbie W, Fryer RG. Are high quality schools enough to close the achievement gap? Evidence from a social experiment in Harlem. 2009.[CrossRef]
  36. Hung M, Smith WA, Voss MW, Franklin JD, Gu Y, Bounsanga J. Exploring student achievement gaps in school districts across the United States. Education and Urban Society. 2020;52(2):175-193.[CrossRef]
  37. Murnane RJ, Willett JB, Bub KL, McCartney K, Hanushek E, Maynard R. Understanding trends in the black-white achievement gaps during the first years of school [with comments]. Brookings-Wharton papers on urban affairs. 2006:97-135.[CrossRef]
  38. Phillips M, Crouse J, Ralph J. Does the black–white test score gap widen after children enter school? 1998;
  39. Rothbart MW. Does school finance reform reduce the race gap in school funding? Education Finance and Policy. 2020;15(4):675-707.[CrossRef]
  40. Talbert-Johnson C. Structural inequities and the achievement gap in urban schools. Education and Urban Society. 2004;37(1):22-36.[CrossRef]
  41. Luthar SS. The culture of affluence: Psychological costs of material wealth. Child development. Nov-Dec 2003;74(6):1581-1593. doi:10.1046/j.1467-8624.2003.00625.x[CrossRef] [PubMed]
  42. Luthar SS, Becker BE. Privileged but pressured? A study of affluent youth. Child development. 2002;73(5):1593-1610.[CrossRef] [PubMed]
  43. Luthar SS, Kumar NL, Zillmer N. High-Achieving Schools Connote Risks for Adolescents: Problems Documented, Processes Implicated, and Directions for Interventions. Am Psychol. Oct 2019;75(7):983-995. doi:10.1037/amp0000556[CrossRef] [PubMed]
  44. Assari S, Caldwell CH. High Risk of Depression in High-Income African American Boys. J Racial Ethn Health Disparities. Aug 2018;5(4):808-819. doi:10.1007/s40615-017-0426-1[CrossRef] [PubMed]
  45. Luthar SS, Barkin SH, Crossman EJ. “I can, therefore I must”: Fragility in the upper-middle classes. Development and Psychopathology. 2013;25(4 0 2):1529.[CrossRef] [PubMed]
  46. Luthar SS, D'AVANZO K. Contextual factors in substance use: A study of suburban and inner-city adolescents. Development and Psychopathology. 1999;11(4):845-867.[CrossRef] [PubMed]
  47. Luthar SS, Sexton CC. The high price of affluence. Advances in child development and behavior. Elsevier; 2004:125-162.[CrossRef] [PubMed]
  48. Luthar SS, Small PJ, Ciciolla L. Adolescents from upper middle class communities: Substance misuse and addiction across early adulthood. Development and psychopathology. 2018;30(1):315-335.[CrossRef] [PubMed]
  49. McMahon TJ, Luthar SS. Patterns and correlates of substance use among affluent, suburban high school students. Journal of Clinical Child and Adolescent Psychology. 2006;35(1):72-89.[CrossRef] [PubMed]
  50. Assari S. Does school racial composition explain why high income black youth perceive more discrimination? A gender analysis. Brain sciences. 2018;8(8):140.[CrossRef] [PubMed]
  51. Assari S. Social Epidemiology of Perceived Discrimination in the United States: Role of Race, Educational Attainment, and Income. Int J Epidemiol Res. Summer 2020;7(3):136-141. doi:10.34172/ijer.2020.24[CrossRef] [PubMed]
  52. Assari S, Caldwell CH. Teacher Discrimination Reduces School Performance of African American Youth: Role of Gender. Brain Sci. Sep 30 2018;8(10)doi:10.3390/brainsci8100183[CrossRef] [PubMed]
  53. Assari S, Cochran SD, Mays VM. Money Protects White but Not African American Men against Discrimination: Comparison of African American and White Men in the Same Geographic Areas. Int J Environ Res Public Health. Mar 8 2021;18(5)doi:10.3390/ijerph18052706[CrossRef] [PubMed]
  54. Assari S, Gibbons FX, Simons RL. Perceived Discrimination among Black Youth: An 18-Year Longitudinal Study. Behav Sci (Basel). Apr 27 2018;8(5)doi:10.3390/bs8050044[CrossRef] [PubMed]
  55. Assari S, Moghani Lankarani M. Workplace racial composition explains high perceived discrimination of high socioeconomic status African American men. Brain sciences. 2018;8(8):139.[CrossRef] [PubMed]
  56. Assari S, Preiser B, Lankarani MM, Caldwell CH. Subjective Socioeconomic Status Moderates the Association between Discrimination and Depression in African American Youth. Brain Sci. Apr 20 2018;8(4)doi:10.3390/brainsci8040071[CrossRef] [PubMed]
  57. Assari S, Zare H. Black-White Differences in The Effects of Parental Education on College Students’ Beliefs about Racial Discrimination. Open Journal of Educational Research. 07/31 2024;4(4):164-173.[CrossRef] [PubMed]
  58. Rodriguez JM, Koo C, Di Pasquale G, Assari S. Black-White differences in perceived lifetime discrimination by education and income in the MIDUS Study in the U.S. J Biosoc Sci. Sep 2023;55(5):795-811. doi:10.1017/s0021932022000360[CrossRef] [PubMed]
  59. Assari S, Boyce S, Caldwell CH, Bazargan M. Parental Educational Attainment and Black-White Adolescents' Achievement Gap: Blacks' Diminished Returns. Open J Soc Sci. Mar 2020;8(3):282-297. doi:10.4236/jss.2020.83026[CrossRef] [PubMed]
  60. Assari S, Mardani A, Maleki M, Boyce S, Bazargan M. Black-White Achievement Gap: Role of Race, School Urbanity, and Parental Education. Pediatric Health Med Ther. 2021;12:1-11. doi:10.2147/PHMT.S238877[CrossRef] [PubMed]
  61. Shervin Assari CHC, Mohsen Bazargan. Parental Educational Attainment and Black-White Adolescents’ Achievement Gap: Blacks’ Diminished Returns. Open Journal of Social Sciences. Mar 2020;8(3):282-297. doi:10.4236/jss.2020.83026[CrossRef] [PubMed]
  62. Assari S. Health disparities due to diminished return among black Americans: Public policy solutions. Social Issues and Policy Review. 2018;12(1):112-145.[CrossRef]
  63. Assari S. Unequal gain of equal resources across racial groups. International journal of health policy and management. 2018;7(1):1.[CrossRef] [PubMed]
  64. Jaeger DA. Reconciling the old and new census bureau education questions: Recommendations for researchers. Journal of Business & Economic Statistics. 1997;15(3):300-309.[CrossRef]
  65. Assari S, Zare H. Unequal Effect of Educational Attainment on Reducing Poverty and Welfare; Diminished Returns of American Indian/Alaska Native Populations. J Rehabil Ther. 2024;6(2):1-11. doi:10.29245/2767-5122/2024/2.1143[CrossRef]
  66. Assari SA, G., Boyce, S., Bazargan, M., Caldwell, C.,. Parental Human Capital and Adolescents’ Executive Function: Immigrants’ Diminished Returns. . Medical Research Archives. 2020;8(10):1-20. doi:10.18103/mra.v8i10.2235[CrossRef] [PubMed]
  67. Bakhtiari E. Diminished returns in Europe: socioeconomic status and ethno-racial health disparities across 30 countries in the European social survey. Journal of Racial and Ethnic Health Disparities. 2022;9(6):2412-2426.[CrossRef] [PubMed]
  68. S A. Minorities Diminished Returns. MedLine Publications. 2020;
  69. Shervin A. Parental Education and Spanking of American Children: Blacks’ Diminished Returns. World journal of educational research (Los Angeles, Calif). 2020;8(2)
  70. Gee GC, Ford CL. STRUCTURAL RACISM AND HEALTH INEQUITIES: Old Issues, New Directions. Du Bois Rev. Apr 2011;8(1):115-132. doi:10.1017/S1742058X11000130[CrossRef] [PubMed]
  71. Gee GC, Hing A, Mohammed S, Tabor DC, Williams DR. Racism and the Life Course: Taking Time Seriously. Am J Public Health. Jan 2019;109(S1):S43-s47. doi:10.2105/ajph.2018.304766[CrossRef] [PubMed]
  72. Gee GC, Walsemann KM, Brondolo E. A life course perspective on how racism may be related to health inequities. Am J Public Health. May 2012;102(5):967-74. doi:10.2105/AJPH.2012.300666[CrossRef] [PubMed]
  73. Paradies Y, Ben J, Denson N, et al. Racism as a Determinant of Health: A Systematic Review and Meta-Analysis. PLoS One. 2015;10(9):e0138511. doi:10.1371/journal.pone.0138511[CrossRef] [PubMed]
  74. Paradies Y, Priest N, Ben J, et al. Racism as a determinant of health: a protocol for conducting a systematic review and meta-analysis. Syst Rev. Sep 23 2013;2:85. doi:10.1186/2046-4053-2-85[CrossRef] [PubMed]
  75. Shariff-Marco S, Breen N, Landrine H, et al. MEASURING EVERYDAY RACIAL/ETHNIC DISCRIMINATION IN HEALTH SURVEYS: How Best to Ask the Questions, in One or Two Stages, Across Multiple Racial/Ethnic Groups? Du Bois Rev. Spring 2011;8(1):159-177. doi:10.1017/S1742058X11000129[CrossRef] [PubMed]
  76. Assari S, Gibbons FX, Simons RL. Perceived discrimination among black youth: An 18-year longitudinal study. Behavioral sciences. 2018;8(5):44.[CrossRef] [PubMed]
  77. Monroe CR. Why are" bad boys" always black?: Causes of disproportionality in school discipline and recommendations for change. The Clearing House: A Journal of Educational Strategies, Issues and Ideas. 2005;79(1):45-50.[CrossRef]
  78. Assari S, Akhlaghipour G, Boyce S, Bazargan M, Caldwell CH. Parental Human Capital and Adolescents’ Executive Function: Immigrants’ Diminished Returns. Medical research archives. 2020;8(10)[CrossRef] [PubMed]
  79. Assari S. Dimensional Change Card Sorting of American Children: Marginalization-Related Diminished Returns of Age. Child Teenagers. 2020;3(2):72-92. doi:10.22158/ct.v3n2p72[CrossRef] [PubMed]
  80. Assari S. Age-Related Decline in Children's Reward Sensitivity: Blacks' Diminished Returns. Res Health Sci. 2020;5(3):112-128. doi:10.22158/rhs.v5n3p112[CrossRef] [PubMed]
  81. Assari S. Parental Education and Nucleus Accumbens Response to Reward Anticipation: Minorities' Diminished Returns. Adv Soc Sci Cult. 2020;2(4):132-153. doi:10.22158/assc.v2n4p132[CrossRef] [PubMed]
  82. Assari S. Mental Rotation in American Children: Diminished Returns of Parental Education in Black Families. Pediatr Rep. Nov 20 2020;12(3):130-141. doi:10.3390/pediatric12030028[CrossRef] [PubMed]
  83. Assari S, Boyce S. Family's Subjective Economic Status and Children's Matrix Reasoning: Blacks' Diminished Returns. Res Health Sci. Nov 29 2021;6(1):1-23. doi:10.22158/rhs.v6n1p1[CrossRef] [PubMed]