Ethnic Bias Research Articles

Ethnic bias in restorative processes? An analysis of access to the police-based national Danish VOM-programme

In this article, possible ethnic bias in access to the national Danish police-based Victim Offender Mediation (VOM) programme is investigated. The analyses of this project show that the VOM personnel informants believe that ethnic minority offenders are underrepresented in this VOM programme. Also, numerous examples of essentialist views on ethnicity and culture emerge among police personnel in the interview and observation data. Yet interestingly, the national VOM participation rates in penal cases analysed for this article show that while young male ethnic minority immigrants are underrepresented in VOM some years, young male ethnic minority descendants are actually overrepresented in VOM meetings.

Ethnic bias and design factors impact response rates of online travel surveys

ABSTRACT Low response rates are pointed as a critical problem in online travel surveys. Tourism researchers need to strive to find ways to increase response rates in order to improve the surveys’ coverage as well as representativeness. Through an experiment, this paper specifically examines the design factors that provide social clues in online survey, and the timing of the solicitation. The results indicated that solicitations sent with a researcher’s Western name induced dramatically more responses (>60%) than did the same solicitation sent with a Chinese name; the attachment of an authoritative title for the Chinese researcher did not mitigate the problem; surveys sent out on Saturday with a reminder on Monday generated the highest response rate; among the variations tested, wording of the solicitation email’s subject line had insignificant impact on response rates. Details of the experiment and an explanation of results based upon underlying social factors are discussed.

Challenging racism in the use of health data

Challenging racism in the use of health data

An examination of consumer bias against female and minority commercial pilots

Several studies have examined biases towards gender and ethnic minorities in professional settings, such as medical practices, academia, and aviation. Our research aims to understand consumers' attitudes towards ethnic minorities and female pilots. A better understanding of the impact of customers' perceptions on these minority groups could improve commercial flight operations and support increasing air travel demands. Specifically, this study investigated consumer perceptions of gender and ethnic bias towards commercial airline pilots and flight students in the United States. In a two-experiment design, participants in Study 1 viewed pictures of current female and male commercial pilots of various races. Participants then rated their opinions on the quality of the pilot (e.g. professionalism, flight safety, smoothness of flight, and their confidence in the pilot). In Study 2, participants viewed pictures of student pilots and rated the individual's likeliness to succeed in flight training. The results indicated that participants favored White male pilots in all conditions and that female and ethnic pilots were generally viewed as less favorable. These findings suggest that overt biases are present towards pilots with implications demonstrating that biases influence the hiring processes for female and minority pilots.

Measuring Ethnic Bias: Can Misattribution-Based Tools from Social Psychology Reveal Group Biases that Economics Games Cannot?

AbstractEconomics games such as the Dictator and Public Goods Games have been widely used to measure ethnic bias in political science and economics. Yet these tools may fail to measure bias as intended because they are vulnerable to self-presentational concerns and/or fail to capture bias rooted in more automatic associative and affective reactions. We examine a set of misattribution-based approaches, adapted from social psychology, that may sidestep these concerns. Participants in Nairobi, Kenya completed a series of common economics games alongside versions of these misattribution tasks adapted for this setting, each designed to detect bias toward noncoethnics relative to coethnics. Several of the misattribution tasks show clear evidence of (expected) bias, arguably reflecting differences in positive/negative affect and heightened threat perception toward noncoethnics. The Dictator and Public Goods Games, by contrast, are unable to detect any bias in behavior toward noncoethnics versus coethnics. We conclude that researchers of ethnic and other biases may benefit from including misattribution-based procedures in their tool kits to widen the set of biases to which their investigations are sensitive.

Ethnic and gender bias in objective structured clinical examination: A critical review

This critical review aimed to synthesize the literature and critique the strength of the methodological quality of current evidence regarding examiner bias related to ethnicity and gender in objective structured clinical examination implemented in health professions education. The Guidelines for Critical Review (GCR) was used to critically appraise the selected studies. Ten studies were retrieved for review. The overall quality of the papers was moderate. Two studies met all the criteria of the GCR, indicating stronger evidence of their outcomes. One of them reported ethnic and gender bias potentially existing, while another found only one examiner showing consistent ethnic bias. No systematic bias was found across the studies. Nonetheless, the possibility of ethnic or gender bias by some examiners cannot be ignored. To mitigate potential examiner bias, the investigation of implicit bias training, frame of reference training, the use of multiple examiners, and combination assessments are suggested.

Rethinking the Approach to Artificial Intelligence for Medical Image Analysis: The Case for Precision Diagnosis.

To date, widely generalizable artificial intelligence (AI) programs for medical image analysis have not been demonstrated, including for mammography. Rather than pursuing a strategy of collecting ever-larger databases in the attempt to build generalizable programs, we suggest three possible avenues for exploring a precision medicine or precision imaging approach. First, it is now technologically feasible to collect hundreds of thousands of multi-institutional cases along with other patient data, allowing stratification of patients into subpopulations that have similar characteristics in the manner discussed by the National Research Council in its white paper on precision medicine. A family of AI programs could be developed across different examination types that are matched to specific patient subpopulations. Such stratification can help address bias, including racial or ethnic bias, by allowing unbiased data aggregation for creation of subpopulations. Second, for common examinations, larger institutions may be able to collect enough of their own data to train AI programs that reflect disease prevalence and variety in their respective unique patient subpopulations. Third, high- and low-probability subpopulations can be identified by application of AI programs, thereby allowing their triage off the radiology work list. This would reduce radiologists' workloads, providing more time for interpretation of the remaining examinations. For high-volume procedures, investigators should come together to define reference standards, collect data, and compare the merits of pursuing generalizability versus a precision medicine subpopulation-based strategy.

Implicit Racial Bias Education and Healthcare Students: A Review of Current Practices

Purpose: Racial disparities in health are well-documented, underscoring the need for health equity education for future healthcare professionals. The goal of this literature review was to examine and describe the interventions, strategies, and an overview of the current evidence-based strategies for implicit bias education of future medical providers. Method: Guided by the exploratory question of discovering the ways Physician Assistant and Medical students are being taught about implicit racial (IR) bias, a search was conducted in PubMed, CINAHL, ERIC, and Google Scholar. Search terms reflected keywords about IR bias education strategies with an intervention and outcome, and PA or medical students within the last 10 years. Results: Of the dozens of peer-reviewed articles on this topic, 12 were chosen for inclusion. Despite heterogeneity in the study designs in this review, there is evidence that healthcare professional student’s exhibit implicit racial or ethnic bias. In both quantitative and qualitative measures, students and faculty consistently and overwhelmingly recognize the importance ofeducation on this topic. Conclusions: There are different types of successful strategies implemented for IR bias education. There is limited and inconclusive research evidence about the impact of IR bias on clinical decision-making due to difficulty in measuring this.

Ethnic Mixing in Early Childhood: Evidence from a Randomized Field Experiment and a Structural Model

We study the social integration of ethnic minority children in the context of an early childhood program conducted in Turkey aimed at preparing 5-year-old native and Syrian refugee children for primary school. We randomly assign children to groups with varying ethnic composition and find that exposure to children of the other ethnicity leads to an increase in the formation of interethnic friendships, especially for Turkish children. We also find that the Turkish language skills of Syrian children are better developed in classes with a larger presence of Turkish children. We then develop a model of friendship formation with two key mechanisms: preference bias and congestion in the friendship formation process. Structural estimation of the model suggests that interethnic exposure reduces the share of own-ethnicity friends (homophily) and has a non-monotonic effect on the propensity to form own-ethnicity friendships beyond what would be expected given the size of the group (inbreeding homophily). Counterfactual analysis indicates that improvement in the language skills of Syrian children can offset more than half of the effect that ethnic bias has on friendship formation patterns. Finally, we find that for Syrian children exposure to Turkish children in the pre-school program has a long-term effect on primary school absenteeism.

A Survey on Deep Learning Face Age Estimation Model: Method and Ethnicity

Face age estimation is a type of study in computer vision and pattern recognition. Designing an age estimation or classification model requires data as training samples for the machine to learn. Deep learning method has improved estimation accuracy and the number of deep learning age estimation models developed. Furthermore, numerous datasets availability is making the method an increasingly attractive approach. However, face age databases mostly have limited ethnic subjects, only one or two ethnicities and may result in ethnic bias during age estimation, thus impeding progress in understanding face age estimation. This paper reviewed available face age databases, deep learning age estimation models, and discussed issues related to ethnicity when estimating age. The review revealed changes in deep learning architectural designs from 2015 to 2020, frequently used face databases, and the number of different ethnicities considered. Although model performance has improved, the widespread use of specific few multi-races databases, such as the MORPH and FG-NET databases, suggests that most age estimation studies are biased against non-Caucasians/non-white subjects. Two primary reasons for face age research’s failure to further discover and understand ethnic traits effects on a person’s facial aging process: lack of multi-race databases and ethnic traits exclusion. Additionally, this study presented a framework for accounting ethnic in face age estimation research and several suggestions on collecting and expanding multi-race databases. The given framework and suggestions are also applicable for other secondary factors (e.g. gender) that affect face age progression and may help further improve future face age estimation research.

Statistical Analysis of Presidential Pardons

This report describes a study of pardon petition evaluations that were performed by the Office of the Pardon Attorney (OPA), a unit in the U.S. Department of Justice that processes thousands of requests for executive clemency each year. A statistical examination was conducted on how OPA screens incoming petitions for technical compliance, investigates the facts underlying each petitioner’s request for clemency, and applies substantive standards for evaluating the merits of such petitions when crafting recommendations to the U.S. President to grant or deny relief. Data were analyzed for any patterns in OPA decisions that indicated statistically significant evidence of racial or ethnic bias.

The Origins and Evolution of Anglo-Kenyan Military Diplomatic Relations Since 1963

Military professionalism has three characteristic: expertise, social responsibility and corporateness. Africa as a continent has faced numerous coup d’etat because of lack of military professionalism, ethnic and tribal biases in recruitment and promotion. Politicization of the military and militarization of politics and legacy of colonialism was perfected by Africans who became military head as their countries got their independence. While the independence period has witnessed cordial diplomatic, trade and economic relations between the two countries, the ideal military professionalism is a key factor in interstate diplomatic relations. Anglo-Kenyan military diplomatic relations have been beset with challenges embedded in military professionalism on both sides. These include challenges in professional training, academic training and character development in terms of military Diplomatic relations. It was, therefore, imperative that this study sought to trace the origin and evolution of Anglo-Kenyan military diplomatic relations since 1963 when Kenya got her independence. The study was informed by realist theory. The study adopted mixed approach which included: historical research design was used while the sample size was 384. The study used simple random sampling method and purposive sampling to distribute 196 KDF and BATUK soldiers across Archer’s Post training area and 188 key stakeholders, key informants and knowledgeable locals (indigenous) and residents in the training area. The instruments used for collecting data from the field were: observation, questionnaires, In-depth interview guide, Archival documents and secondary data. Data were analyzed with the aid of statistical package for social sciences software (SPSS) version 27. The finding is presented in prose. The findings were: Kenya soveignity is compromised by the permanent BATUK bases in the country. Eavesdropping by BATUK a foreign troop poses a threat to Kenya’s national security. British had three major interests in Kenya which were: to ensure that Kenya remained socially, economically and politically friendly to Britain, the retention of “forward basing”.

Achieving a Diverse, Equitable, and Inclusive Environment for the Black Orthopaedic Surgeon: Part 1: Barriers to Successful Recruitment of Black Applicants.

Achieving a Diverse, Equitable, and Inclusive Environment for the Black Orthopaedic Surgeon: Part 1: Barriers to Successful Recruitment of Black Applicants.

Cross‐ethnicity face anti‐spoofing recognition challenge: A review

Face anti-spoofing is critical to prevent face recognition systems from a security breach. The biometrics community has %possessed achieved impressive progress recently due the excellent performance of deep neural networks and the availability of large datasets. Although ethnic bias has been verified to severely affect the performance of face recognition systems, it still remains an open research problem in face anti-spoofing. Recently, a multi-ethnic face anti-spoofing dataset, CASIA-SURF CeFA, has been released with the goal of measuring the ethnic bias. It is the largest up to date cross-ethnicity face anti-spoofing dataset covering $3$ ethnicities, $3$ modalities, $1,607$ subjects, 2D plus 3D attack types, and the first dataset including explicit ethnic labels among the recently released datasets for face anti-spoofing. We organized the Chalearn Face Anti-spoofing Attack Detection Challenge which consists of single-modal (e.g., RGB) and multi-modal (e.g., RGB, Depth, Infrared (IR)) tracks around this novel resource to boost research aiming to alleviate the ethnic bias. Both tracks have attracted $340$ teams in the development stage, and finally 11 and 8 teams have submitted their codes in the single-modal and multi-modal face anti-spoofing recognition challenges, respectively. All the results were verified and re-ran by the organizing team, and the results were used for the final ranking. This paper presents an overview of the challenge, including its design, evaluation protocol and a summary of results. We analyze the top ranked solutions and draw conclusions derived from the competition. In addition we outline future work directions.

Diversity, Equity, and Inclusion: A strategic priority for the American Pediatric Surgical Association

Diversity, Equity, and Inclusion: A strategic priority for the American Pediatric Surgical Association

Acting Wisely: Eliminating Negative Bias in Medical Education-Part 1: The Fundamentals.

Bias is a ubiquitous problem in human functioning. It has plagued medical decision making, making physicians prone to errors of perception and judgment. Racial, gender, ethnic, and religious negative biases infest physicians' perception and cognition, causing errors of judgment and behavior that are damaging. In Part 1 of this series of 2 papers, the authors address the problem of harmful bias, the science of cognition, and what is known about how bias functions in human perception and information processing. They lay the groundwork for an approach to reducing negative bias through awareness, reflection, and bias mitigation, an approach in which negative biases can be transformed-by education, experience, practice, and relationships-into positive biases toward one another. The authors propose wisdom as a conceptual framework for imagining a different way of educating medical students. They discuss fundamental cognitive, affective, and reflective components of wisdom-based education. They also review the skills of awareness, using debiasing strategies, compassion, fostering positive emotion, and reflection that are inherent to a wisdom-based approach to eliminating the negative effects of bias in medical education. In Part 2, the authors answer a key question: How can medical educators do better? They describe the interpersonal, structural, and cultural elements supportive of a wisdom-based learning environment, a culture of respect and inclusion in medical education.

‘Those people who chose us’: Discursive construction of identity and belonging in the context of Quebec’s 2018 provincial elections

In the climate of the growing diversification of the ethnocultural landscape, Quebecers of French-Canadian background, often viewed as mistrustful of ethnic minorities, have been faced with the challenge of renegotiating the symbolic boundaries of what it means to be a Quebecer. This study investigates discursive construction of identity and belonging in a multi-text body of discourse generated in the context of the French-language party leader debates in the run-up to Quebec’s 2018 provincial elections, which brought to power the center-right Coalition Avenir Québec. A close textual analysis of discourse produced by the party leaders and by debate viewers commenting on the Facebook page of Radio-Canada during the debates’ live stream, following the research program of Critical Discourse Analysis, demonstrates an enduring ethnic bias in the conceptualization of Quebec identity by the dominant ingroup – Francophone Quebecers of French-Canadian origin – one that puts in jeopardy the inclusive, civic Quebec identity promoted in official discourse of the Quebec government.

Characterization of the 2019 Micrographic Surgery and Dermatologic Oncology Standardized Letter of Recommendation

BACKGROUND Traditional letters of recommendation used for postgraduate medical training applications have multiple limitations, including a lack of clarity, inflated and overly flattering assessments, and low reliability between interpreting faculty. A micrographic surgery and dermatologic oncology (MSDO) standardized letter of recommendation (SLOR) was created to improve the efficiency, validity, and stratification of applicants to dermatology fellowship training programs. OBJECTIVE To analyze the MSDO SLOR for trends in grading based on letter-writer and applicant characteristics and to evaluate its ability to demonstrate differences between applicants. METHODS Standardized letter of recommendations received by 4 fellowship programs from the 2019 San Francisco Match application cycle were reviewed retrospectively. RESULTS Two hundred forty-nine SLORs were analyzed from 140 applicants. Grade inflation and limited variability in scores were evident. Higher scores correlated with the length of the relationships between letter-writers and applicants and with female letter-writer gender. There was no applicant gender or ethnicity bias detected. CONCLUSION Despite score inflation, the MSDO SLOR allows for differentiation between fellowship applicants. Future studies are needed to further evaluate the reliability of the SLOR and find ways to improve its content.

The Press Sectarian Crisis And Violence Against Women İn Plateau State Nigeria A Critical Evaluation

In most societies, women and girls are victims of war and violence. More often than not, during sectarian crises or escalating hostilities, they are sexually abused and left to suffer the brunt. With the aid of Human Rights Consciousness Journalism Theoretical Framework, this qualitative study “The Press, Sectarian Crisis and Violence against Women on the Plateau: A Critical Evaluation” investigated the matter in Plateau State, Nigeria. It found that ethnic and religious bias, lack of objective reportage and failure of international media are likely responsible for the failure of the press to bring an end to the orgy of violence against women in the state. The study recommended recruiting more women journalists, thorough reportage of women-related issues and proactive measures by female-journalists as possible panacea to the lingering cases of violence against women in Plateau. It concluded that given their rightful place in the media industry, women could reduce the menacing effects of gender-based violence. That way, the press would be exonerated from complicity in reporting women-in-conflict in Plateau State, Nigeria and beyond.

ETHNIC BIAS, FAVORITISM AND DEVELOPMENT IN AFRICA

The leadership in many African Countries with their ethnic diversities is characterized by ethnic bias and favoritism and citizens are thus treated unequally in many respects, particularly when it comes to national resource allocation and political representation. This breads resentment and creates conditions for an ultimate rejection of the state by the frustrated and politically conscious masses. It is also a tantamount to corruption there by weakening the ability of the state to function efficiently and is therefore anti-developmental. In this paper, it argues that the socio economic crises in many African countries are aggravated by practices of ethnic Bias and favoritism that have consistently violated the principle of the impersonality of economic agents caused by resentment among the marginalized ethnic groups fuelled conflict and retarded development on the Continent. It is also recommended that a strong and credible judicial body with powers to investigate crimes against citizens and prosecute & punish offenders be established by the African Union.