Racial Bias Research Articles

Mandatory age verification for pornography access: Why it can't and won't ‘save the children’

Age verification is currently gaining traction among some western democracies as a means to restrict minors’ access to online pornography. In this article we consider the ramifications of applying age estimation software to this task. We analyse a public dataset of 10,139 facial images processed through a commonly used high-performance convolutional neural network approach and find significant inconsistencies in classification performance. Notably, the software demonstrates racial bias, with highest accuracy for the Caucasian category and lowest accuracy for the African category. It also displays age and gender bias, with lower accuracy for young males compared to young females. In addition to underwhelming technical performance, we argue that the concept of employing automated processes to restrict access to pornography is not only problematic but fundamentally misconceived. The systems being proposed to automate age verification create greater user data privacy risks and divert resourcing that could be spent on strategies that are proven to support healthy sexual development. Ultimately, mandatory age verification systems create barriers to post-pubescent young people seeking information about sex online. Our study concludes that the underlying problem with age verification, therefore, is not only technical but more profoundly political: even if the system can be made to work, it should not be.

Does racial and gender bias shape perception: examining how other’s pro-environmental behaviors are viewed

ABSTRACT The current work explores how individuals perceive others’ pro-environmental behaviors. Actions do not occur in isolation but within societal structures that provide schemas shaping interpretations of the perceived behaviors. This research utilizes the theoretical framework of Pierre Bourdieu with an emphasis on symbolic capital, power, and violence as to why perceptions may differ. Differences in perception can reflect societal views on sex, race, or any other socially important characteristic. Using a novel survey design, a national sample of United States respondents (n = 1,218) randomly rated 32 pro-environmental behavior vignettes-actor pairings. Through the comparison of means and multivariate regression analyses, significant differences regarding the level of perceived concern emerge. Findings highlight that Black, Indigenous, and People of Color, along with women pro-environmental actors, are perceived to display lower levels of environmental concern through their actions. Additionally, being white or a man tends to enhance the reported level of concern demonstrated. Comparable environmental behaviors should be rated similarly. However, those possessing specific symbolic capital (e.g. race or gender) may be viewed in higher esteem by most, if not all, regarding their level of concern. Ultimately, this can lead to benefits for some and further marginalization for others.

Race-Conscious Teacher Coaching: Disrupting Implicit Bias and Improving Teachers’ Relationships with Black Students

ABSTRACT Racial discipline disproportionality is a persistent issue in schools with Black students experiencing exclusionary discipline two to three times more than their White peers, and Black males more likely to be diagnosed with an emotional and behavioral disorder. Interventions that target malleable root causes of disproportionality and have an explicit racial bias component may disrupt these processes. The study took place in an alternative school setting across two classrooms with White, fifth- and sixth-grade teachers (n = 2) and their Black students (n = 6). A single-case, withdrawal design (A-B-A-B) examined the impact of a semi-structured teacher coaching intervention on disrupting biases, improving classroom management and cultural competency, and ultimately improving student-teacher relationships. The coaching included Mindful STOP as a self-regulation strategy, the Mindful Reflection Protocol to discuss behaviors, and performance feedback, all focusing on outcomes related to student-teacher relationships and discipline. During intervention phases, Teacher 1 showed improvements in positive communication while keeping negative communication low. Teacher 2 showed smaller, more variable improvements. Teachers and students in both classrooms reported improvements in their relationships based on pre/post rating scales. Teacher-reported discipline outcomes were variable. These findings may provide concrete strategies for supporting the development of equitable discipline practices for Black students. Future studies will explore modifications to the current coaching package.

Understanding the Influence of Single Bias Reduction Strategies on Personal and Systemic Bias Outcomes

Social psychological research has used strategies to increase recognition of and motivation to combat personal or systemic bias, but with little attention to whether single strategies might influence both personal and systemic outcomes. We investigated whether single strategies are effective in both bias domains and potential underlying mechanisms. Across two experiments, non-Black participants were exposed to information concerning (a) their personal racial biases, (b) multiple Black individuals’ discrimination experiences across institutional contexts, or (c) race-unrelated information (control condition). Discrimination experiences exposure (vs. control) increased recognition of systemic bias and motivation to combat both systemic and personal bias (Studies 1 and 2), and we found statistical support for empathy as a mediator (Study 2). In contrast, strategies for highlighting personal bias had weaker effects on personal bias outcomes and no effects on systemic bias outcomes. We discuss theoretical and practical implications of discrimination experiences exposure for combatting systemic and personal bias.

Evaluating a novel high-density EEG sensor net structure for improving inclusivity in infants with curly or tightly coiled hair

Electroencephalography (EEG) is an important tool in the field of developmental cognitive neuroscience for indexing neural activity. However, racial biases persist in EEG research that limit the utility of this tool. One bias comes from the structure of EEG nets/caps that do not facilitate equitable data collection across hair textures and types. Recent efforts have improved EEG net/cap design, but these solutions can be time-intensive, reduce sensor density, and are more difficult to implement in younger populations. The present study focused on testing EEG sensor net designs over infancy. Specifically, we compared EEG data quality and retention between two high-density saline-based EEG sensor net designs from the same company (Magstim EGI, Whitland, UK) within the same infants during a baseline EEG paradigm. We found that within infants, the tall sensor nets resulted in lower impedances during collection, including lower impedances in the key online reference electrode for those with greater hair heights and resulted in a greater number of usable EEG channels and data segments retained during pre-processing. These results suggest that along with other best practices, the modified tall sensor net design is useful for improving data quality and retention in infant participants with curly or tightly-coiled hair.

Is gender dysphoria associated with increased hospital cost per stay among patients hospitalized for depression? Focus on the racial and regional variance in US hospitals

IntroductionIndividuals with gender dysphoria do not identify with their sex assigned at birth and face societal and cultural challenges, leading to increased risk for depression, anxiety, and suicide. Gender dysphoria is a DSM-5 diagnosis but is not necessary for transition therapy. Additionally, individuals with gender dysphoria or who identify as gender diverse/nonconforming may experience “minority stress” from increased discrimination, leading to a greater risk for mental health problems. This study aimed to identify possible health disparities in patients hospitalized for depression with gender dysphoria across the United States. Depression was selected because patients with gender dysphoria are at an increased risk for it. Various patient and hospital-related factors are explored for their association with changes in healthcare utilization for patients hospitalized with depression.MethodsThe National Inpatient Sample was used to identify nationwide patients with depression (n = 378,552, weighted n = 1,892,760) from 2016 to 2019. We then examined the characteristics of the study sample and investigated how individuals’ gender dysphoria was associated with healthcare utilization measured by hospital cost per stay. Multivariate survey regression models were used to identify predictors.ResultsAmong the 1,892,760 total depression inpatient samples, 14,145 (0.7%) patients had gender dysphoria (per ICD-10 codes). Over the study periods, depression inpatients with gender dysphoria increased, but total depression inpatient rates remained stable. Survey regression results suggested that gender dysphoria, minority ethnicity or race, female sex assigned at birth, older ages, and specific hospital regions were associated with higher hospital cost per stay than their reference groups. Sub-group analysis showed that the trend was similar in most racial and regional groups.ConclusionDifferences in hospital cost per stay for depression inpatients with gender dysphoria exemplify how this community has been disproportionally affected by racial and regional biases, insurance denials, and economic disadvantages. Financial concerns can stop individuals from accessing gender-affirming care and risk more significant mental health problems. Increased complexity and comorbidity are associated with hospital cost per stay and add to the cycle.

Eliciting cognitive consistency increases acceptance of implicit bias.

Resistance to knowledge about implicit bias jeopardizes the ability to learn, understand, and act to outsmart bias. Across three experiments and five independent samples (N > 3,500), conditions that increase cognitive consistency were created alongside control conditions. In Experiment 1, using a race (Black-White) Implicit Association Test (IAT), cognitive consistency was enhanced when participants evaluated the validity and utility of the test before, rather than after, receiving the test result, leading to greater acceptance of bias. In Experiments 2 and 3, participants either evaluated their performance on a Black-White IAT alone or evaluated their performance on a morally innocuous Insect-Flower IAT prior to a Black-White IAT. Again, resistance to evidence of implicit racial bias was reduced in the latter condition, where the imperative for cognitive consistency was heightened. In all three experiments, creating ordinary conditions to heighten cognitive consistency was associated with increased bias awareness and acceptance and, additionally, with support for actions to minimize its consequence-outcomes critical to achieving effective bias education. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Racial and ethnic disparities post-hospitalization for COVID-19: barriers to access to care for survivors of COVID-19 acute respiratory distress syndrome

Racial and ethnic health disparities in the incidence and severity of Coronavirus Disease 2019 (COVID-19) have been observed globally and in the United States. Research has focused on transmission, hospitalization, and mortality among racial and ethnic minorities, but Long COVID-19 health disparities research is limited. This study retrospectively evaluated 195 adults who survived COVID-19 associated acute respiratory distress syndrome (C-ARDS) in New York City from March–April 2020. Among survivors, 54% met the criteria for Long COVID syndrome. Hispanic/Latinx patients, were more likely to be uninsured (p = 0.027) and were less frequently discharged to rehabilitation facilities (p < 0.001). A cross-sectional telephone survey and interview were conducted with a subset of survivors (n = 69). Among these, 11% reported a lack of follow-up primary care post-discharge and 38% had subsequent emergency room visits. Notably, 38% reported poor treatment within the health care system, with 67% attributing this to racial or ethnic bias. Thematic analysis of interviews identified four perceived challenges: decline in functional status, discrimination during hospitalization, healthcare system inequities, and non-healthcare-related structural barriers. Sources of resilience included survivorship, faith, and family support. This study highlights structural and healthcare-related barriers rooted in perceived racism and poverty as factors impacting post-COVID-19 care.

Emotion expression salience and racially biased weapon identification: A diffusion modeling approach.

Racial stereotypes are commonly activated by informational cues that are detectable in people's faces. Here, we used a sequential priming task to examine whether and how the salience of emotion (angry/scowling vs. happy/smiling expressions) or apparent race (Black vs. White) information in male face primes shapes racially biased weapon identification (gun vs. tool) decisions. In two experiments (Ntotal = 546) using two different manipulations of facial information salience, racial bias in weapon identification was weaker when the salience of emotion expression versus race was heightened. Using diffusion decision modeling, we tested competing accounts of the cognitive mechanism by which the salience of facial information moderates this behavioral effect. Consistent support emerged for an initial bias account, whereby the decision process began closer to the "gun" response upon seeing faces of Black versus White men, and this racially biased shift in the starting position was weaker when emotion versus race information was salient. We discuss these results vis-à-vis prior empirical and theoretical work on how facial information salience moderates racial bias in decision-making.

Ethnic‐racial socialization in Chinese American immigrant families: Associations with middle childhood ethnic identity

AbstractCompared to studies of ethnic identity development in adolescence, fewer investigations have examined the development of ethnic identity during middle childhood, a developmental period of dynamic social and cognitive changes that have direct implications for social identity and group membership. Moreover, research on the developmental processes of Asian American youth has also primarily utilized cross‐group comparisons, while neglecting consideration of variations in acculturation, socioeconomic status, and other sociodemographic characteristics within Asian American ethnic groups. Using a socioeconomically‐ and acculturatively‐diverse sample of Chinese immigrant families in the United States (N = 169; 49.1% girls; M = 9.16 years; SD = 1.05), the present study examined how parents’ ERS practices varied by parents’ socioeconomic status, education, and cultural orientations, then tested associations between parents’ ERS and children's self‐reported ethnic centrality and ethnic regard. More highly‐educated Chinese American immigrant parents reported more frequent cultural socialization and more acculturated parents reported more preparation of their children for racial and ethnic bias. Consistent with hypotheses, parents’ cultural socialization was positively associated with children's self‐reported ethnic centrality and positive regard. Results highlight the roles of social status and acculturation in Chinese immigrant parents’ ERS, and point to middle childhood as a key developmental window for ethnic identity socialization and development in immigrant families.

Beyond Size and Accuracy: The Impact of Model Compression on Fairness

Model compression is increasingly popular in the domain of deep learning. When addressing practical problems that use complex neural network models, the availability of computational resources can pose a significant challenge. While smaller models may provide more efficient solutions, they often come at the cost of accuracy. To tackle this problem, researchers often use model compression techniques to transform large, complex models into simpler, faster models. These techniques aim to reduce the computational cost while minimizing the loss of accuracy. The majority of the model compression research focuses exclusively on model accuracy and size/speedup as performance metrics. This paper explores how different methods of model compression impact the fairness/bias of a model. We conducted our experiments using the COMPAS Recidivism Racial Bias dataset. We evaluated a variety of model compression techniques across multiple bias groups. Our findings indicate that the type and amount of compression have substantial impact on both the accuracy and fairness/bias of the model.

The influence of face mask color on perceptions of African American and white men

Despite their widespread use during the COVID-19 pandemic, face masks hinder abilities to interpret facial expressions. Yet, they can also reduce the appearance of characteristics that are used to categorize individuals into racial groups, such as Afrocentric features. The color of a face mask might also promote associations with certain types of behavior and professional occupations (e.g., blue surgical mask connoting physician stereotypes; black masks potentially being associated with criminality). This study assessed whether the presence and color of a face mask impacted perceptions of a target male of varying race. White participants (N = 250) were presented with an African American or White male adult face from the Chicago Face Database (of equal age and attractiveness) wearing a blue or black surgical mask, or no mask (Photoshopped onto the face) and rated the man on emotions (happy, sad, angry) as well as how trustworthy, threatening, and attractive the target appeared. Targets wearing a blue surgical mask were judged as more trustworthy and attractive than those wearing no mask (perhaps due to association with medical professions), but these judgements were not qualified by race, despite the African American target’s selection based on Afrocentric features. The color black on a face mask did not exacerbate negative perceptions of targets, perhaps suggesting a decline effect in previously demonstrated associations between this color and criminal actions. Unlike previous research performed at the beginning of the Covid-19 Pandemic on cloth masks shown to potentially exacerbate racial biases, surgical masks (pleated and made of polymeric materials), appear to lessen potential stereotyping of Black relative to White men.

Advancing Equity: Understanding, Addressing, and Mitigating Bias in Assessment in Medical Education.

Despite the growing presence of women and historically underrepresented groups in academic medicine, significant disparities remain. This article examines a key aspect of these disparities: biases in assessment and learning environments. Reviewing current literature, including in OBGYN, reveals persistent gender and racial biases in subjective clinical narrative assessments. The paper then outlines a 2-pronged approach for change: first, enhancing the learning environment, and subsequently, providing targeted recommendations for individuals, academic leaders, and healthcare institutions to effectively address these biases.

Evaluating precision medicine tools in cystic fibrosis for racial and ethnic fairness.

Patients with cystic fibrosis (CF) experience frequent episodes of acute decline in lung function called pulmonary exacerbations (PEx). An existing clinical and place-based precision medicine algorithm that accurately predicts PEx could include racial and ethnic biases in clinical and geospatial training data, leading to unintentional exacerbation of health inequities. We estimated receiver operating characteristic curves based on predictions from a nonstationary Gaussian stochastic process model for PEx within 3, 6, and 12 months among 26,392 individuals aged 6 years and above (2003-2017) from the US CF Foundation Patient Registry. We screened predictors to identify reasons for discriminatory model performance. The precision medicine algorithm performed worse predicting a PEx among Black patients when compared with White patients or to patients of another race for all three prediction horizons. There was little to no difference in prediction accuracies among Hispanic and non-Hispanic patients for the same prediction horizons. Differences in F508del, smoking households, secondhand smoke exposure, primary and secondary road densities, distance and drive time to the CF center, and average number of clinical evaluations were key factors associated with race. Racial differences in prediction accuracies from our PEx precision medicine algorithm exist. Misclassification of future PEx was attributable to several underlying factors that correspond to race: CF mutation, location where the patient lives, and clinical awareness. Associations of our proxies with race for CF-related health outcomes can lead to systemic racism in data collection and in prediction accuracies from precision medicine algorithms constructed from it.

Acceptability of Racial Microaggressions From the Perspective of Speech-Language Pathology Students.

Implicit racial and ethnic biases have been documented across a variety of allied health professions; however, minimal research on this topic has been conducted within the field of speech-language pathology. The purpose of this study was to understand implicit racial and ethnic bias in speech-language pathology students by examining their perceptions and attitudes about the acceptability of racial and ethnic microaggressions. We also examined whether the student ratings varied by their racial and ethnic identity (White vs. people of color [POC]). Fifty-nine students (72% White, 28% POC) currently enrolled in a speech-language pathology program voluntarily completed the Acceptability of Racial Microaggressions Scale via an online Qualtrics survey. Although 70% of the student ratings classified the microaggressive statements as unacceptable, 30% of their ratings classified the statements as either (a) acceptable or (b) neither acceptable nor unacceptable. Although both groups of students rated the majority of statements as unacceptable, students who self-identified as White rated more statements as acceptable than students who self-identified as POC. Findings indicating relatively high rejection of microaggressive statements by speech-language pathology students are promising. However, responses were not uniform, and a nontrivial proportion of responses provided by speech-language pathology students reflected passivity toward or active endorsement of microaggressive statements.

Understanding the Interplay of Race in the Criminal Justice System

Purpose: The purpose of this study was to investigate and understand the interplay of race in the criminal justice system. Methodology: The study adopted a desktop research methodology. Desk research refers to secondary data or that which can be collected without fieldwork. Desk research is basically involved in collecting data from existing resources hence it is often considered a low cost technique as compared to field research, as the main cost is involved in executive’s time, telephone charges and directories. Thus, the study relied on already published studies, reports and statistics. This secondary data was easily accessed through the online journals and library. Findings: The findings reveal that there exists a contextual and methodological gap relating to the interplay of race, class and gender in the criminal justice system. Preliminary empirical review revealed that that pervasive racial disparities exist within this institution, as evidenced by disproportionate treatment of racial minorities at various stages of the criminal justice process. It found that despite efforts to promote fairness and equity, implicit biases and systemic racism continued to influence decision-making, leading to disparities in arrests, prosecutions, and sentencing. The study highlighted the interconnectedness of race with other social factors such as socioeconomic status and neighborhood characteristics and underscored the urgency of implementing evidence-based interventions and policy reforms to address racial disparities effectively. Recommendations included diversifying law enforcement agencies, implementing implicit bias training programs, and reforming sentencing guidelines to promote fairness and reduce disparities in incarceration rates. Unique Contribution to Theory, Practice and Policy: The Critical Race theory, Labeling theory and Structural Functionalism may be used to anchor future studies on the interplay between race and the outcomes within criminal justice. The study provided recommendations that contributed to theory, practice, and policy. It integrated critical race theory into the analysis to explore systemic racism's role in perpetuating racial disparities. Practically, evidence-based policing strategies and procedural justice principles were emphasized, alongside community policing initiatives and accountability measures to address bias and misconduct. Policy recommendations included reforming sentencing laws, investing in alternatives to incarceration, and addressing social determinants of crime. The study contributed to theory by examining intersecting identities' impact and advocated for community-driven interventions, trauma-informed approaches, and reforms to reduce racial bias and enhance accountability within the criminal justice system.

Racial Bias in Pediatric Pain Perception

Racial disparities in pediatric pain care are prevalent across a variety of health care settings, and likely contribute to broader disparities in health, morbidity, and mortality. The present research expands on prior work demonstrating potential perceptual contributions to pain care disparities in adults and tests whether racial bias in pain perception extends to child targets. We examined the perception and hypothetical treatment of pain in Black and White boys (experiment 1), Black and White boys and girls (experiment 2), Black and White boys and adult men (experiment 3), and Black, White, Asian, and Latinx boys (experiment 4). Across this work, pain was less readily perceived on Black (vs White) boys’ faces—though this bias was not observed within girls. Moreover, this perceptual bias was comparable in magnitude to the same bias measured with adult targets and consistently predicted bias in hypothetical treatment. Notably, bias was not limited to Black targets—pain on Hispanic/Latinx boys’ faces was also relatively underperceived. Taken together, these results offer strong evidence for racial bias in pediatric pain perception. PerspectiveThis article demonstrates perceptual contributions to racial bias in pediatric pain recognition. Participants consistently saw pain less readily on Black boys’ faces, compared with White boys, and this perceptual bias consistently predicted race-based gaps in treatment. This work reveals a novel factor that may support pediatric pain care disparities.

Influence of Gender Stereotypes in Hiring Decisions

Purpose: The aim of the study was to investigate the influence of gender stereotypes in hiring decisions. Methodology: The study adopted a desktop research methodology. Desk research refers to secondary data or that which can be collected without fieldwork. Desk research is basically involved in collecting data from existing resources hence it is often considered a low cost technique as compared to field research, as the main cost is involved in executive’s time, telephone charges and directories. Thus, the study relied on already published studies, reports and statistics. This secondary data was easily accessed through the online journals and library. Findings: The findings reveal that there exists a contextual and methodological gap relating to the influence of gender stereotypes in hiring decisions. Preliminary empirical review revealed that gender bias significantly influenced hiring processes, favoring male candidates over equally qualified female candidates. Through an analysis of empirical evidence from various studies conducted by scholars, it was evident that gender stereotypes intersected with other forms of discrimination, such as racial or ethnic bias, exacerbating disparities in employment opportunities, particularly for women of color. Despite increasing awareness of the importance of diversity, gender bias persisted, hindering progress towards gender parity in the workplace. Recommendations included implementing blind recruitment processes and diversity training to address bias and promote transparency in hiring practices, facilitating the creation of more equitable and inclusive workplaces. Unique Contribution to Theory, Practice and Policy: Social Role Theory, Ambivalent Sexism theory and Intersectionality theory may be used to anchor future studies on influence of gender stereotypes in hiring decisions. The study provided several recommendations that contributed to theory, practice, and policy. It emphasized the need to raise awareness of gender bias, suggested implementing structural changes like blind recruitment, advocated for diversity and inclusion initiatives, highlighted the role of organizational culture, and called for the involvement of policymakers in addressing systemic barriers. These recommendations aimed to promote fairness, equity, and diversity in employment practices within STEM and beyond, contributing to theoretical understanding, informing practical strategies, and shaping policy interventions.

Reducing racial bias in scientific communication: Journal policies and their influence on reporting racial demographics.

Research titles with White samples, compared to research titles with samples of color, have been less likely to include the racial identity of the sample. This unequal writing practice has serious ramifications for both the history and future of psychological science, as it solidifies in the permanent scientific record the false notion that research with White samples is more generalizable and valuable than research with samples of color. In the present research, we experimentally tested the extent to which PhD students (63% White students, 27% students of color) engaged in this unequal writing practice, as well as the extent to which this practice might be disrupted by journal policies. In Study 1, PhD students who read about research conducted with a White sample, compared to those who read about the exact same research conducted with a Black sample, were significantly less likely to mention the sample's racial identity when generating research titles, keywords, and summaries. In Study 2, PhD students instructed to mention the racial identity of their samples, and PhD students instructed to not mention the identity of their samples (though to a lesser extent), were less likely to write about the White versus Black samples unequally. Across both studies, we found that PhD students were overall supportive of a policy to make the racial demographics of samples more transparent, believing that it would help to reduce racial biases in the field. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Discovering racial bias in algorithms: The case of ferritin prediction

Discovering racial bias in algorithms: The case of ferritin prediction