Many of our common-sense moral judgments seemingly imply the existence of moral luck. I attempt to avoid moral luck while retaining most of these judgments. I defend a view on which agents have moral ...equality of opportunity. This allows us to account for our anti-moral-luck intuitions at less cost than has been previously recognized.
One of the great paradoxes of inequality in organizations is that even when organizations introduce new programs designed to help employees in traditionally disadvantaged groups succeed, employees ...who use these programs often suffer negative career consequences. This study helps to fill a significant gap in the literature by investigating how local employer practices can enable employees to successfully use the programs designed to benefit them. Using a research approach that controls for regulatory environment and program design, we analyze unique longitudinal personnel data from a large law firm to demonstrate that assignment to powerful supervisors upon organization entry improves career outcomes for individuals who later use a reduced-hours program. Additionally, we find that initial assignment to powerful supervisors is more important to positive career outcomes—that is, employee retention and performance-based pay—than are factors such as supervisor assignment at the time of program use. Initial assignment affects career outcomes for later program users through the mechanism of improved access to reputation-building work opportunities. These findings have implications for research on work-family programs and other employee-rights programs and for the role of social capital in careers.
What factors influence levels of repression targeting refugee populations? In this paper, we explore the efficacy of top-down and bottom-up approaches to mitigating host-state repression, ...specifically highlighting the role of human rights organizations (HROs) and institutionalized equal opportunity in influencing states’ decision to violently repress refugees. In so doing, we argue that repression levels can be moderated through proper accommodation and integration of refugee populations via the activities of HROs in addition to increased institutionalized equal opportunities for displaced persons. Using a new dataset that captures state repression of refugee populations together with a zero-inflated ordered probit model and an estimation technique that addresses endogeneity, we find mixed support for our hypotheses.
Managerial bias is a major source of workplace inequality and a central target of employer diversity efforts, yet we know little about the content of stereotypes and where they prevail. Stereotypes ...can be ambivalent, mixing negative and positive dimensions. Ambivalent stereotypes can rationalize discriminatory decision-making but they may also be more amenable to change. This article examines the prevalence of wholly negative and ambivalent age-based stereotypes across organizational contexts. Data on 551 managers reveals, first, that the modal manager holds ambivalent stereotypes about older workers, with positive perceptions of their personal attributes and negative perceptions regarding their employability. Second, both negative and ambivalent stereotypes are common in the presence of a labour union. Their prevalence declines, however, in different contexts: ambivalent stereotypes decline with increased intergroup contact and negative stereotypes decline when accountability triggers are implmented. Implications for research on work, organizations, older workers, and diversity management are discussed.
PurposeThe purpose of the study is to examine if the existing legislative framework in Trinidad and Tobago supports equal opportunities and the achievement of fundamental human rights for persons ...with disabilities seeking to access education, employment, accommodations and goods and services.Design/methodology/approachData were collected from 105 complaints filed with Trinidad and Tobago's Equal Opportunity Commission from 2010 to 2021 regarding disability discrimination. The steps of constant comparison were used to analyse characteristics of each case, complainants' desired outcomes and the actual outcomes of the cases (i.e. withdrawn, closed, forwarded to conciliation or the Equal Opportunity Tribunal).FindingsAcross all cases, persons with disabilities desired access to unavailable services, opportunities for employment or an apology for emotional distress. Cases that were withdrawn reflected missed opportunities to address systemic issues, closed cases reflected a bounded process for redress, and cases advancing to conciliation or the Tribunal required documentation or support.Originality/valueThis study provides insights into how the current policy and its implementation miss opportunities to address discrimination at organisational and systemic levels. Specifically, cases revealed dominant/subordinate dynamics in society and a lack of transparency throughout the system. Authors provide recommendations for policy and systemic change, including addressing gaps in national legislation and adopting strong equality of opportunity and equality of well-being approaches.
Predictive bias (i.e., differential prediction) means that regression equations predicting performance differ across groups based on protected status (e.g., ethnicity, sexual orientation, sexual ...identity, pregnancy, disability, and religion). Thus, making prescreening, admissions, and selection decisions when predictive bias exists violates principles of fairness based on equal treatment and opportunity. First, we conducted a two-part study showing that different types of predictive bias exist. Specifically, we conducted a Monte Carlo simulation showing that out-of-sample predictions provide a more precise understanding of the nature of predictive bias-whether it is based on intercept and/or slope differences across groups. Then, we conducted a college admissions study based on 29,734 Black and 304,372 White students, and 35,681 Latinx and 308,818 White students and provided evidence about the existence of both intercept- and slope-based predictive bias. Third, we discuss the nature and different types of predictive bias and offer analytical work to explain why each type exists, thereby providing insights into the causes of different types of predictive bias. We also map the statistical causes of predictive bias onto the existing literature on likely underlying psychological and contextual mechanisms. Overall, we hope our article will help reorient future predictive bias research from whether it exists to the why of different types of predictive bias.
La présente contribution entend mettre à l’épreuve la rhétorique de l’égalité des chances à l’université Omar Bongo de Libreville au regard des conditions d’études et de vie des étudiants. Dans cette ...perspective, la question qui sert de fil d’Ariane au présent projet de connaissance est celle de savoir comment parler d’égalité des chances dans un contexte marqué par différentes formes de précarité. Pour y répondre, l’approche méthodologique s’articule autour d’une analyse de contenu des discours politiques croisée à un examen des statistiques officielles.
This contribution is intended to test the rhetoric of equal opportunity at Omar Bongo University in Libreville with regard to the conditions of study and life of students. From this perspective, the question that serves as a guideline for this knowledge project is how to talk about equal opportunities in a context marked by various forms of precariousness. In order to answer this question, the methodological approach is based on a content analysis of political discourse cross-referenced with an examination of official statistics.
La dualité du système d’enseignement supérieur français -universités et grandes écoles-implique de nombreuses inégalités que s’efforcent de combattre les politiques. Depuis le début des années 1980, ...l’égalité des chances est au cœur de toutes les réformes éducatives et la priorité est donnée à la lutte contre les inégalités qu’elles soient de genre, sociales, culturelles ou géographiques. Partant de là, l’objectif de ce travail est d’analyser les effets de ces diverses réformes sur l’évolution des inégalités d’accès à l’enseignement supérieur, notamment l’accès aux formations prestigieuses. On estime une régression logistique multinomiale pour comparer les bases Génération 1998 et 2013 du Céreq en se focalisant sur quatre vecteurs d’inégalités : genre, origines culturelle, géographique et sociale. Nos résultats montrent que malgré la réduction de certaines inégalités, l’accès aux diverses orientations de l’enseignement supérieur et notamment l’accès aux formations prestigieuses, demeure très marqué par les inégalités, notamment de genre et sociales.
The French higher education system is characterized by a dual system -universities and “elite schools”- which is at the root of many inequalities that politics try to fight against. Since the 1980s, equal opportunities were at the heart of all educational reforms and the fight against inequalities became the priority whether they are gendered, geographical, social or cultural. Starting from this point, the aim of this work is to analyze the effects of the various reforms on the evolution of the inequalities of access to higher education especially with regard to prestigious courses. We use a multinomial logistic regression to compare the Cereq database Generation 1998 and 2013 focusing on four vectors of inequalities: gender, social, cultural and geographical inequalities. Our results show that in spite of a reduction of some inequalities, access to various areas of higher education and more particularly access to prestigious and selective training courses, remains affected by inequalities, in particular by gender and social inequalities.
By its very definition, "health equity"-a state where every community has an equal opportunity to thrive-is for everyone. No community should face unjust and avoidable barriers to the basic, vital ...conditions1 (humane housing, reliable transportation, quality health care, etc.) we all need to be healthy and well. Nor is health equity a zero-sum game with winners and losers: we all stand to gain. Yet despite the universal benefit, finding common ground for the kinds of laws and policies that would achieve health equity seems impossible given our entrenched political divides. As a result, health equity remains an ideal for some future, better, and healthier United States.That future will be shaped not only by those of us currently in political power but also by generations to follow, starting with Generation Z (Gen Z). Of late, much has been made about that group's burgeoning political muscle. In recent elections, young voters have "connected the dots between movement insurgency and voter mobilization" in ways that "could be a game changer."2In December 2022, the Association of American Medical Colleges, Center for Health Justice conducted a nationally representative poll of members of Gen Z, aged 18-24years, to identify emerging areas of multiracial, bipartisan, cross-geography and -demography consensus on topics relevant to achieving health equity.3 Given current political debates, we were surprised by unexpected areas of agreement among these younger self-identified Democrats, Independents, and Republicans.
One of the main concerns about fairness in machine learning (ML) is that, in order to achieve it, one may have to trade off some accuracy. To overcome this issue, Hardt et al. (Adv Neural Inf Process ...Syst 29, 2016) proposed the notion of equality of opportunity (EO), which is compatible with maximal accuracy when the target label is deterministic with respect to the input features. In the probabilistic case, however, the issue is more complicated: It has been shown that under differential privacy constraints, there are data sources for which EO can only be achieved at the total detriment of accuracy, in the sense that a classifier that satisfies EO cannot be more accurate than a trivial (i.e., constant) classifier. In this paper, we strengthen this result by removing the privacy constraint. Namely, we show that for certain data sources, the most accurate classifier that satisfies EO is a trivial classifier. Furthermore, we study the admissible trade-offs between accuracy and EO loss (opportunity difference) and characterize the conditions on the data source under which EO and non-trivial accuracy are compatible.
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