Scientists explain the underrepresentation of women in physics compared to biology in four national contexts
Autor/in:
Chan, Esther; Di Di; Ecklund, Elaine Howard
Quelle: Gend Work Organ (Gender, Work and Organization), (2023)
Inhalt: Women are consistently underrepresented in biology when compared to physics. Yet how scientists themselves explain the causes of this underrepresentation is understudied outside the US context. In this research, we ask the following question: How do scientists in different national/regional contexts explain why there are fewer women in physics than biology? Using original survey data collected among academic biologists and physicists in the US (N = 1777), Italy (N = 1257), France (N = 648), and Taiwan (N = 780), we examine how scientists' social identities, social locations, and country context shape essentialist, individualist, and structural explanations of gender inequality. Findings indicate that scientists across national contexts attribute the unequal gender distribution in physics and biology to women's individual choices. Explanations for the gender distribution also vary by social identities and social locations (gender, discipline, and seniority) in country-specific ways. Scientists and advocates ought to engage conversations that explicitly confront scientists' assumptions about individual choices in global science.
Quelle: Front. Sociol. (Frontiers in Sociology), 8 (2023) , 1154138 S
Inhalt: Gender segregation in higher education is considered one of the main drivers of persistent economic gender inequality. Yet, though there has been considerable research identifying and describing the underlying mechanisms that cause gendered educational choices in higher education, little is known about how gender segregation in higher education could be changed. Accordingly, this article aims to determine the potential of educational interventions during high school to foster gender desegregation in higher education. We focused on two different processes that contribute to gender segregation in majors among higher education graduates: first, the selection into specific majors and, second, the selection out of specific majors. We investigated whether an intensive counselling programme leads to more gender-atypical choices among high-school graduates and examined whether intensive counselling supports several indicators of students' persistence in gender-atypical majors. Based on data from an experimental study of a counselling programme for German high-school students (N = 625), we estimated the programme's effect with linear probability models and intention-to-treat analysis. Our results show that high-school graduates are more likely to choose a gender-atypical major if they have received intensive counselling. This applies more to men than to women. In addition, the programme improved some persistence indicators for students in gender-atypical majors. Although we found a significant programme effect only for perceived person-major fit and student satisfaction, the coefficients of all aspects of students' persistence show a trend indicating that the programme was beneficial for students in gender-atypical majors. As experimental studies can also be affected by various types of bias, we performed several robustness checks. All analyses indicated stable results. In conclusion, we suggest that intensive counselling programmes have the potential to reduce gender segregation in higher education. More students were motivated to choose a gender-atypical major, and different aspects of student persistence were supported by the programme for students in gender-atypical majors.
Schlagwörter:Beratung; college major choice; gender segregation; horizontal segregation; horizontale Segregation; Studienberatung; Studienfachwahl; Studium
CEWS Kategorie:Naturwissenschaft und Technik, Studium und Studierende
Anti-Sexism Alert System: Identification of Sexist Comments on Social Media Using AI Techniques
Autor/in:
Díaz Redondo, Rebeca P. Díaz; Fernández Vilas, Ana Fernández; Ramos Merino, Mateo Ramos; Valladares Rodríguez, Sonia María Valladares; Torres Guijarro, Soledad Torres; Hafez, Manar Mohamed
Quelle: Applied Sciences, 13 (2023) 7, 4341 S
Inhalt: Social relationships in the digital sphere are becoming more usual and frequent, and they constitute a very important aspect for all of us. Violent interactions in this sphere are very frequent, and have serious effects on the victims. Within this global scenario, there is one kind of digital violence that is becoming really worrying: sexism against women. Sexist comments that are publicly posted in social media (newspaper comments, social networks, etc.), usually obtain a lot of attention and become viral, with consequent damage to the persons involved. In this paper, we introduce an anti-sexism alert system, based on natural language processing (NLP) and artificial intelligence (AI), that analyzes any public post, and decides if it could be considered a sexist comment or not. Additionally, this system also works on analyzing all the public comments linked to any multimedia content (piece of news, video, tweet, etc.) and decides, using a color-based system similar to traffic lights, if there is sexism in the global set of posts. We have created a labeled data set in Spanish, since the majority of studies focus on English, to train our system, which offers a very good performance after the validation experiments.
Schlagwörter:artificial intelligence; Big Data; method; prevention; sexism; Social Media; violence against women
Quelle: Data & Knowledge Engineering, 143 (2023) , 102108 S
Inhalt: Gender inclusion is fundamental to a prosperous society, but inequality and exclusion persist in various sectors of it. One of them is the ICT field, which is still struggling to represent the diversity of those it serves. The lack of diversity and power imbalance in software development affects the produced systems, that, instead of advancing gender inclusion, create new barriers in achieving it. Although considered neutral, software does not equally serve everyone who depends on it, favoring characteristics that are statistically more observed in those that are represented during development. As software development teams are predominantly male, it is not surprising that existing systems favor characteristics that are statistically more observed in men over characteristics observed in other genders. As technologies rapidly evolve and revolutionize the way we live, addressing this problem becomes urgent to ensure that these systems benefit everyone, regardless of their gender. As a first step towards this goal, we performed a systematic mapping study on gender issues in software engineering whose results indicated that gender impacts development and systems, but there are limited approaches for addressing it in Requirements Engineering. This study served as the foundation for proposing a conceptual model for gender-inclusive requirements. Its main objective is to facilitate discussion and analysis of gender and related concepts in the elicitation process to include them in the specification of requirements. In this paper, we extend this work by illustrating the concepts with an example, by presenting a process for using the knowledge of the model and a prototype tool that implements it, and by discussing an evaluation with 31 participants of the conceptual model’s usefulness, difficulty of understanding, strengths and weaknesses, use and recommendation, and finally, its components. The results were positive as both novices and experts in conceptual modeling considered the model useful, provided comprehensive feedback on its strengths but also suggestions for improvement, and most answered positively to the questions about whether they would use and recommend it
Diversity, Equity, and Inclusion in Artificial Intelligence: An Evaluation of Guidelines
Autor/in:
Cachat-Rosset, Gaelle; Klarsfeld, Alain
Quelle: Applied Artificial Intelligence, 37 (2023) 1, 2176618 S
Inhalt: ABSTRACTArtificial intelligence (AI) is present everywhere in the lives of individuals. Unfortunately, several cases of discrimination by AI systems have already been reported. Scholars have warned on risks of AI reproducing existing inequalities or even amplifying them. To tackle these risks and promote responsible AI, many ethics guidelines for AI have emerged recently, including diversity, equity, and inclusion (DEI) principles and practices. However, little is known about the DEI content of these guidelines, and to what extent they meet the most relevant accumulated knowledge from DEI literature. We performed a semi-systematic literature review of the AI guidelines regarding DEI stakes and analyzed 46 guidelines published from 2015 to today. We fleshed out the 14 DEI principles and the 18 DEI practices recommended underlying these 46 guidelines. We found that the guidelines mostly encourage one of the DEI management paradigms, namely fairness, justice, and nondiscrimination, in a limited compliance approach. We found that narrow technical practices are favored over holistic ones. Finally, we conclude that recommended practices for implementing DEI principles in AI should include actions aimed at directly influencing AI actors? behaviors and awareness of DEI risks, rather than just stating intentions and programs.
Schlagwörter:artificial intelligence; Big Data; method; text analysis
CEWS Kategorie:Diversity, Frauen- und Geschlechterforschung
Exploring Gender Bias in Six Key Domains of Academic Science: An Adversarial Collaboration
Autor/in:
Ceci, Stephen J.; Kahn, Shulamit; Williams, Wendy M.
Quelle: Psychological science in the public interest : a journal of the American Psychological Society, (2023)
Inhalt: We synthesized the vast, contradictory scholarly literature on gender bias in academic science from 2000 to 2020. In the most prestigious journals and media outlets, which influence many people's opinions about sexism, bias is frequently portrayed as an omnipresent factor limiting women's progress in the tenure-track academy. Claims and counterclaims regarding the presence or absence of sexism span a range of evaluation contexts. Our approach relied on a combination of meta-analysis and analytic dissection. We evaluated the empirical evidence for gender bias in six key contexts in the tenure-track academy: (a) tenure-track hiring, (b) grant funding, (c) teaching ratings, (d) journal acceptances, (e) salaries, and (f) recommendation letters. We also explored the gender gap in a seventh area, journal productivity, because it can moderate bias in other contexts. We focused on these specific domains, in which sexism has most often been alleged to be pervasive, because they represent important types of evaluation, and the extensive research corpus within these domains provides sufficient quantitative data for comprehensive analysis.
Contrary to the omnipresent claims of sexism in these domains appearing in top journals and the media, our findings show that tenure-track women are at parity with tenure-track men in three domains (grant funding, journal acceptances, and recommendation letters) and are advantaged over men in a fourth domain (hiring). For teaching ratings and salaries, we found evidence of bias against women; although gender gaps in salary were much smaller than often claimed, they were nevertheless concerning. Even in the four domains in which we failed to find evidence of sexism disadvantaging women, we nevertheless acknowledge that broad societal structural factors may still impede women's advancement in academic science. Given the substantial resources directed toward reducing gender bias in academic science, it is imperative to develop a clear understanding of when and where such efforts are justified and of how resources can best be directed to mitigate sexism when and where it exists.
Unlocking the Power of Mentoring : A Comprehensive Guide to Evaluating the Impact of STEM Mentorship Programs for Women
Autor/in:
Wolf, Elke; Brenning, Stefanie
Quelle: Soc. Sci. (Social Sciences), 12 (2023) 9
Inhalt: Although mentoring programs for female STEM students are often carried out with a great deal of passion on the part of program managers and mentors, robust results on their effects are often missing. However, regular evaluations are indispensable for an efficient allocation of resources towards gender balances in STEM. To accomplish this requirement, empirically valid and easy-to-use evaluation concepts are needed. We therefore develop an evaluation concept which corresponds to a Logic Chart, capturing three levels of expected effects (output—outcome—impact). On each level of impact, we derive a set of success indicators that can be measured by qualitative methods. A major advantage of our evaluation design is that the effect of a mentoring program can be observed directly after the end of the program. Furthermore, the results provide information about different channels of impact (e.g., reduced stereotypes or increased self-efficacy) and hence offer concrete indications for the further development of the program.
Cross-national variations in postdoc precarity: An inquiry into the role of career structures and research funding models
Autor/in:
O’Connor, Pat; Le Feuvre, Nicky; Sümer, Sevil
Quelle: Policy Futures in Education, (2023)
Inhalt: Insecurity and intense competition for permanent academic positions appear to be common experiences for early career researchers across the globe. With academic precarity now firmly on the international research and policy agenda, this article looks comparatively at postdoc precarity in three European countries: Ireland, Norway and Switzerland. It suggests that the career prospects and status of these early career stage researchers depend to a large extent on societal variations in academic career structures and research funding models. The article underlines the implications of an increasingly competitive academic labour market on postdoc precarity and identifies both common and specific (national and/or disciplinary) challenges facing postdocs in these different contexts.
Schlagwörter:career structures; early career researcher; international comparison; internationaler Vergleich; Post-doc; precarity; prekäre Beschäftigung; research funding; wissenschaftliche Karriere
CEWS Kategorie:Europa und Internationales, Wissenschaft als Beruf