The gender wage gap Blau, Francine D; Kahn, Lawrence M
Journal of economic literature,
09/2017, Letnik:
55, Številka:
3
Journal Article
Recenzirano
Odprti dostop
Using Panel Study of Income Dynamics (PSID) microdata over the 1980–2010 period, we provide new empirical evidence on the extent of and trends in the gender wage gap, which declined considerably ...during this time. By 2010, conventional human capital variables taken together explained little of the gender wage gap, while gender differences in occupation and industry continued to be important. Moreover, the gender pay gap declined much more slowly at the top of the wage distribution than at the middle or bottom and by 2010 was noticeably higher at the top. We then survey the literature to identify what has been learned about the explanations for the gap. We conclude that many of the traditional explanations continue to have salience. Although human-capital factors are now relatively unimportant in the aggregate, women's work force interruptions and shorter hours remain significant in high-skilled occupations, possibly due to compensating differentials. Gender differences in occupations and industries, as well as differences in gender roles and the gender division of labor remain important, and research based on experimental evidence strongly suggests that discrimination cannot be discounted. Psychological attributes or noncognitive skills comprise one of the newer explanations for gender differences in outcomes. Our effort to assess the quantitative evidence on the importance of these factors suggests that they account for a small to moderate portion of the gender pay gap, considerably smaller than, say, occupation and industry effects, though they appear to modestly contribute to these differences.
Big Data's Disparate Impact Barocas, Solon; Selbst, Andrew D.
California law review,
06/2016, Letnik:
104, Številka:
3
Journal Article
Recenzirano
Advocates of algorithmic techniques like data mining argue that these techniques eliminate human biases from the decision-making process. But an algorithm is only as good as the data it works with. ...Data is frequently imperfect in ways that allow these algorithms to inherit the prejudices of prior decision makers. In other cases, data may simply reflect the widespread biases that persist in society at large. In still others, data mining can discover surprisingly useful regularities that are really just preexisting patterns of exclusion and inequality. Unthinking reliance on data mining can deny historically disadvantaged and vulnerable groups full participation in society. Worse still, because the resulting discrimination is almost always an unintentional emergent property of the algorithm's use rather than a conscious choice by its programmers, it can be unusually hard to identify the source of the problem or to explain it to a court. This Essay examines these concerns through the lens of American antidiscrimination law—more particularly, through Title VII's prohibition of discrimination in employment. In the absence of a demonstrable intent to discriminate, the best doctrinal hope for data mining's victims would seem to lie in disparate impact doctrine. Case law and the Equal Employment Opportunity Commission's Uniform Guidelines, though, hold that a practice can be justified as a business necessity when its outcomes are predictive of future employment outcomes, and data mining is specifically designed to find such statistical correlations. Unless there is a reasonably practical way to demonstrate that these discoveries are spurious, Title VII would appear to bless its use, even though the correlations it discovers will often reflect historic patterns of prejudice, others' discrimination against members of protected groups, or flaws in the underlying data. Addressing the sources of this unintentional discrimination and remedying the corresponding deficiencies in the law will be difficult technically, difficult legally, and difficult politically. There are a number of practical limits to what can be accomplished computationally. For example, when discrimination occurs because the data being mined is itself a result of past intentional discrimination, there is frequently no obvious method to adjust historical data to rid it of this taint. Corrective measures that alter the results of the data mining after it is complete would tread on legally and politically disputed terrain. These challenges for reform throw into stark relief the tension between the two major theories underlying antidiscrimination law: anticlassification and antisubordination. Finding a solution to big data's disparate impact will require more than best efforts to stamp out prejudice and bias; it will require a wholesale reexamination of the meanings of "discrimination" and "fairness."
Gender-based discrimination (GBD) creates a hostile environment that can affect medical students. Mentorship has been recognized as a mitigating factor for GBD. We aimed to investigate the impacts of ...GBD on career selection and well-being of medical students in Brazil and to explore access to mentorship among these students.
A cross-sectional study was performed using an anonymous survey in Portuguese. The survey was distributed in June 2021 to students enrolled in Brazilian medical schools. It contained 24 questions, including demographics, episodes of GBD experienced by responders and their impact on professional and personal life, and mentorship access.
Of 953 respondents, 748 (78%) were cisgender women, 194 (20%) cisgender men, and 11 nonbinary (1%). Sixty-six percent (625/953) of students reported experiencing GBD, with cisgender women and nonbinary being more likely to experience it than cisgender men (P < 0.001). Responders who experiences GBD report moderate to severe impact on career satisfaction (40%, 250/624), safety (68%, 427/624), self-confidence (68%, 426/624), well-being (57%, 357/625), and burnout (62%, 389/625). Cisgender women were more likely to report these effects than men counterparts (P < 0.01). Only 21% of respondents (201/953) had mentors in their medical schools.
Our findings demonstrate that GBD is widespread among Brazilian medical students affecting their personal and professional lives, and most of them do not have access to a mentor. There is an urgent need to increase access to mentors who could mitigate the adverse effects of GBD and help develop a diverse and inclusive medical workforce.
The gender imbalance in STEM subjects dominates current debates about women's underrepresentation in academia. However, women are well represented at the Ph.D. level in some sciences and poorly ...represented in some humanities (e.g., in 2011, 54% of U.S. Ph.D.'s in molecular biology were women versus only 31% in philosophy). We hypothesize that, across the academic spectrum, women are underrepresented in fields whose practitioners believe that raw, innate talent is the main requirement for success, because women are stereotyped as not possessing such talent. This hypothesis extends to African Americans' underrepresentation as well, as this group is subject to similar stereotypes. Results from a nationwide survey of academics support our hypothesis (termed the field-specific ability beliefs hypothesis) over three competing hypotheses.
•We present a meta-analysis of ethnic discrimination in rental housing market.•Minority and male applicants are discriminated.•Gender discrimination is greater for minority than for majority ...applicants.•Real-estate agents discriminate significantly less than private landlords do.•Private landlords display significant statistical discrimination.
We present a broad review of all studies having tested for discrimination against minority ethnic groups in the rental housing market by the correspondence testing method. We perform a meta-analysis of correspondence tests from 25 separate studies conducted in OECD countries between 2006 and 2017, containing more than 300 estimates of effects and representing a total of more than 110,000 e-mails sent to private landlords or real-estate agents. In addition to presenting overall results of recent studies, we focus on subgroups of specific correspondence tests in order to highlight the differences in ethnicity, gender, type of landlords, procedure, continent, and type of information provided in applications. We provide evidence that both gender and ethnic discrimination occur in the rental housing market in OECD countries, such that applicants with minority-sounding names and male names are discriminated against (especially Arab/Muslim applicants). Thus, ethnic majority women are the most favored in this market in OECD countries while minority men are the most disadvantaged. Moreover, we show the existence of interactions between ethnic and gender discrimination: gender discrimination is greater for minority-sounding names than for majority-sounding names. Finally, it seems that real-estate agents discriminate significantly less against minority applicants than private landlords do. This would seem to be at least in part because private landlords display significant statistical discrimination while real-estate agents do not. These results are robust to the estimation methods used (random effects, fixed-effects, and unrestricted weighted least squares methods).
Intersectional insights and frameworks are put into practice in a multitude of highly contested, complex, and unpredictable ways. We group such engagements with intersectionality into three loosely ...defined sets of practices: applications of an intersectional framework or investigations of intersectional dynamics; debates about the scope and content of intersectionality as a theoretical and methodological paradigm; and political interventions employing an intersectional lens. We propose a template for fusing these three levels of engagement with intersectionality into a field of intersectional studies that emphasizes collaboration and literacy rather than unity. Our objective here is not to offer pat resolutions to all questions about intersectional approaches but to spark further inquiry into the dynamics of intersectionality both as an academic frame and as a practical intervention in a world characterized by extreme inequalities. At the same time, we wish to zero in on some issues that we believe have occupied a privileged place in the field from the very start, as well as on key questions that will define the field in the future. To that end, we foreground the social dynamics and relations that constitute subjects, displacing what often seems like an undue emphasis on the subjects (and categories) themselves as the starting point of inquiry. We also situate the development and contestation of these focal points of intersectional studies within the politics of academic and social movements—which, we argue, are themselves deeply intersectional in nature and therefore must continually be interrogated as part of the intersectional project.
In this article, I build a new line of health inequality research that parallels the emerging structural racism literature. I develop theory and measurement for the concept of structural sexism and ...examine its relationship to health outcomes. Consistent with contemporary theories of gender as a multilevel social system, I conceptualize and measure structural sexism as systematic gender inequality at the macro level (U.S. state), meso level (marital dyad), and micro level (individual). I use U.S. state-level administrative data linked to geocoded data from the NLSY79, as well as measures of inter-spousal inequality and individual views on women’s roles as predictors of physical health outcomes in random-effects models for men and women. Results show that among women, exposure to more sexism at the macro and meso levels is associated with more chronic conditions, worse self-rated health, and worse physical functioning. Among men, macro-level structural sexism is also associated with worse health. However, greater meso-level structural sexism is associated with better health among men. At the micro level, internalized sexism is not related to physical health among either women or men. I close by outlining how future research on gender inequality and health can be furthered using a structural sexism perspective.
The presentation of sleep disorders varies widely among women and men, and sleep disorders among women are frequently subject to under- and delayed diagnosis. Insomnia is a complex sleep disorder ...with a multifactorial etiology, and women face many sex-specific sleep health challenges that may contribute to and influence the presence of insomnia symptoms across their lifespan. These include sex differences in neurobiology, hormonal variation during menstruation, pregnancy and menopause, increased prevalence of mood disorders, increased vulnerability to adverse socioeconomic factors, and gender discrimination, among other psychosocial stressors, particularly among women of racial-ethnic minority. As the medical community continues to recognize the significance of sleep as a vital pillar of overall wellbeing, the integration of sex-specific considerations in research, diagnosis, and treatment strategies is essential to optimizing sleep health for women.
This study examines the role of responsible entrepreneurship among female entrepreneurs by examining how and when responsible entrepreneurship may exert a positive influence on female entrepreneurial ...success. Using the data collected from 337 Chinese female entrepreneurs, and by integrating responsible entrepreneurship research with a dynamic capability framework, our findings show, firstly, that responsible entrepreneurship is positively correlated to female entrepreneurial success; secondly, this relationship is mediated by female entrepreneurs’ opportunity recognition; and thirdly, the indirect effect of responsible entrepreneurship on female entrepreneurial success through opportunity recognition is weaker when women entrepreneurs perceive more gender discrimination. Furthermore, using a post hoc analysis, we find that responsible entrepreneurship has a positive impact on entrepreneurial success for both male and female entrepreneurs, but that this impact is more significant for female entrepreneurs than for their male counterparts. With the contextual factor of traditional female social stereotypes inadvertently contributing to greater gender discrimination in the field of entrepreneurship, our results underscore the importance of both responsible entrepreneurship and opportunity recognition in promoting female entrepreneurial success.
In this paper, we provide a broad, integrative review of the degree to which gender inequities exist in organizational domains and practices covering areas such as performance evaluation, ...compensation, leadership, work-family conflict, and sexual harassment, spanning the employee lifecycle from selection to exiting the organization. Where the literature allows, we review intersectionality findings. We also review the factors and processes that facilitate and hinder gender equity in the workplace, by drawing on the most robust empirical evidence. Throughout the paper, we distinguish between findings that allow us to infer gender inequity versus gender equality. Consolidating these disparate literatures allows us to develop a model that explains how gender inequities cumulate across the employee lifecycle and are reinforced across multiple levels (i.e., societal, organizational, interpersonal, and individual). We also identify important gaps in the literature, suggest next steps for research and highlight practical implications for organizations aiming to advance gender equity.
•A comprehensive review of gender inequities in the workplace is provided.•Gender differences in the workplace arise from inequitable treatment and outcomes.•Gender inequities accumulate across the employee lifespan and at multiple levels.•Intersectionality effects are reviewed, revealing inconsistent patterns.•Directions for future research are provided.
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