Infrequent Identity Signals, Multiple Correspondence, and Detection Risks in Audit Correspondence Studies

Audit correspondence studies are field experiments that test for discriminatory behavior in active markets. Researchers measure discrimination by comparing how responsive individuals (“audited units”) are to correspondences from different types of people. This article elaborates on the tradeoffs researchers face between sending audited units only one correspondence and sending them multiple correspondences, especially when including less common identity signals in the correspondences. We argue that when researchers use audit correspondence studies to measure discrimination against individuals that infrequently interact with audited units, they raise the risk that these audited units become aware they are being studied or otherwise act differently. We also argue that sending multiple pieces of correspondence can increase detection risk. We present the result of an audit correspondence study that demonstrates how detection can occur for these reasons, leading to significantly attenuated (biased toward zero) estimates of discrimination.

Assédio sexista no ambiente acadêmico e o caso midiatizado da UFCG: as redes sociais como aliadas na militância online

O assédio sexista — comportamento discriminatório por sexo ou gênero, expondo alguém a uma situação degradante —,traz consequências negativas também no ambiente acadêmico. Este artigo analisa a circulação da notícia de um caso de assédio ocorrido na Universidade Federal de Campina Grande (UFCG) em outubro de 2020, a partir de comentários no Instagram. Para tanto, reconstitui o caso midiatizado, mostrando os circuitos de circulação e as consequências para o desenlace do fato. A base teórica traz conceitos de midiatização e circulação. Como resultados, tem-se que as enunciações nesses circuitos culminaram num movimento de militância online para a tomada de decisões por parte das autoridades acadêmicas.Sexist harassment in the academic environment and the mediated case of UFCG: social networks as allies in online militancyAbstractSexist harassment — discriminatory behavior by sex or gender, exposing someone to a degrading situation — has negative consequences also in the academic environment. This article analyzes the circulation of news about a case of harassment that occurred at the Federal University of Campina Grande (UFCG) in October 2020, based on comments on Instagram. Therefore, it reconstructs the mediatized case, showing the circulation circuits and consequences for the outcome of the fact. The theoretical basis brings concepts of mediatization and circulation. As a result, we have that the enunciations in these circuits culminated in an online militancy movement for decisionmaking by academic authorities.Keywords: Social networks; mediatized case; ciculatino circuits; online militancy; scheduling.

How Communicating about Discrimination Influences Attributions of Blame and Condemnation

Across two randomized experiments, we examine how communication about discriminatory acts can influence judgments of blame and condemnation. Specifically, we consider whether attributing discrimination to implicit or explicit bias affects how people evaluate online reports of discrimination. In Study 1 (N = 947), we explore this question in the context of an online news environment, and in Study 2 (N = 121) we replicate our results on a social media site (i.e., Twitter). Across both studies, we document how viewers respond differently to reports of discrimination due to variation in agent motives, the type of bias that purportedly caused the discriminatory behavior, and the extent to which agents are reported to have completed implicit bias training. We discuss our theoretical contribution to perspectives of blame attribution and the communication of bias as well as the practical implications of our findings.

Positive Exemplar Exposure

In adults, implicit racial bias has been linked to prejudiced and discriminatory behavior. However, implicit racial biases emerge well before adulthood; as young as age six, children have already internalized the racial attitudes of their culture. Thus, it is critical for researchers to understand how to change implicit racial bias early in development, before its negative effects compound across the lifespan. The following chapter highlights one potential method of bias reduction in childhood: exposure to positive exemplars. As this method is both scalable and child-friendly, it has the potential to be used with young children on a broader cultural level. This chapter details child-friendly methods for measuring bias change and provides two examples of studies that have successfully employed positive exemplar exposure to reduce children’s implicit racial bias. I conclude the chapter with recommendations for future use of this intervention cross-culturally, as well as broader cultural applications.

Back to “normal”: the short-lived impact of an online NGO campaign of government discrimination in Hungary

To what extent can civil rights NGOs protect ethnic minorities against unequal treatment? We study this question by combining an audit experiment of 1260 local governments in Hungary with an intervention conducted in collaboration with a major Hungarian civil rights NGO. In the audit experiment we demonstrated that Roma individuals were about 13 percent-points less likely to receive responses to information requests from local governments, and the responses they received were of substantially lower quality. The intervention that reminded a random subset of local governments of their legal responsibility of equal treatment led to a short-term reduction in their discriminatory behavior, but the effects of the intervention dissipated within a month. These findings suggest that civil rights NGOs might face substantive difficulties in trying to reduce discrimination through simple information campaigns.

Using a social marketing approach to develop a pro-diversity intervention

Purpose Despite more than half a century of academic research, relatively few methods have been shown to reliably improve intergroup relations in the real world. This paper aims to use a social marketing approach to design a pro-diversity intervention in a university setting. Design/methodology/approach We conducted extensive qualitative, quantitative and observational background research to identify elements that would increase the effectiveness of the intervention. Focus groups and surveys allowed us to identify a target audience, target behaviors and the relevant barriers and benefits. Findings The background research suggested increasing inclusive behavior would have a greater impact than reducing discriminatory behavior. Based on this research, this paper determined an optimal target audience was students who had relatively positive attitudes toward diversity but engaged in few inclusive behaviors. This paper used relevant theories from the behavioral sciences to design an intervention that promoted a small set of inclusive behaviors and that addressed the relevant barriers and benefits. The intervention took the form of a single page of targeted messages that instructors can add to their course syllabi. The page communicates injunctive and descriptive norms, highlights the benefits of behaving inclusively and provides concrete behavioral advice. Originality/value The research applies the social marketing approach to a novel domain. This approach represents a new way to advance diversity, equity and inclusion through promoting inclusive and reducing discriminatory behavior.

Nursing Students' Experiences of Educational Discrimination: A Qualitative Study

Background: Although the need for justice and the elimination of injustice (or discrimination) is now a universally accepted principle, discrimination is still an unpleasant experience for many nursing students. This study aimed to explain the experiences of nursing students of educational discrimination and find out the main factors that cause this feeling.Methods: This is a qualitative study conducted in the nursing faculty of Shahr-e-Kord and the Iran university of medical science (IUMS) in Iran. Twelve nursing students were selected by purposeful sampling method and were interviewed. All interviews were analyzed according to the content analysis method.Results: Three main themes and ten subcategories appeared. Extracted themes include: "inappropriate behavior of nursing professors (or instructors) " with 3 subcategories (1- discriminatory behavior by nursing professors (or instructors), 2- lack of sufficient self-confidence in nursing professors and transferring it to the student, and 3- the educator role in motivating or eliminating motivation); "Strict rules" with 3 subcategories (1- inequality in implementation of rights and rules among students of different disciplines, 2- differences in compliance with laws and regulations, and 3- nurses are being strictly monitored), and " Lack of nursing professional independence " with 4 subcategories (1- lack of authority, 2- lack of supportive organizations for nurses, 3- lack of proper social status of nursing in society, and 4- the high authority and power of physicians over other disciplines).Conclusions: In our study, it was shown that nursing students feel the most discrimination in front of medical students. Feelings of discrimination reduce self-confidence in nursing students. Therefore, nursing educators and professors must think of a solution, or at least they themselves should not cause this feeling in them by inappropriate behavior and discriminatory speech and words.

Constitutional equality in the information society: the problem of private discrimination

The article deals with the implementation of constitutional norms on equality in the information society, which stimulates the manifestation of private and economic discrimination. Threats arising from the existence of natural inequalities have been investigated. On the basis of the conclusion about the legal admissibility of private discrimination, social and legal grounds for the implementation of the constitutional principle of equality have been revealed. The differentiation of private and economic discrimination is proposed, factors are identified that must be considered when determining the admissibility of discriminatory behavior in the information society: the level of market monopolization, the negotiating capabilities of the parties, the amount of costs required to restore the violated right. Considering the insufficiency of the actual capabilities of consumers of information benefits, it is concluded that it is necessary to protect the weak side of information relations. Movement to the minimum possible level of discretion on the side of provider of informational goods and creation of additional legal guarantees for constitutional and other rights of the citizen is provided.

A Survey on Bias and Fairness in Machine Learning

With the widespread use of artificial intelligence (AI) systems and applications in our everyday lives, accounting for fairness has gained significant importance in designing and engineering of such systems. AI systems can be used in many sensitive environments to make important and life-changing decisions; thus, it is crucial to ensure that these decisions do not reflect discriminatory behavior toward certain groups or populations. More recently some work has been developed in traditional machine learning and deep learning that address such challenges in different subdomains. With the commercialization of these systems, researchers are becoming more aware of the biases that these applications can contain and are attempting to address them. In this survey, we investigated different real-world applications that have shown biases in various ways, and we listed different sources of biases that can affect AI applications. We then created a taxonomy for fairness definitions that machine learning researchers have defined to avoid the existing bias in AI systems. In addition to that, we examined different domains and subdomains in AI showing what researchers have observed with regard to unfair outcomes in the state-of-the-art methods and ways they have tried to address them. There are still many future directions and solutions that can be taken to mitigate the problem of bias in AI systems. We are hoping that this survey will motivate researchers to tackle these issues in the near future by observing existing work in their respective fields.