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1. An Empirical Investigation on the Challenges Faced by Women in the Software Industry: A Case Study

   https://doi.org/10.1109/ICSE-SEIS55304.2022.9793931  

   Trinkenreich, Bianca ; Britto, Ricardo ; Gerosa, Marco ; Steinmacher, Igor ( June 2022 , 2022 IEEE/ACM 44th International Conference on Software Engineering: Software Engineering in Society (ICSE-SEIS))

   Context: Addressing women's under-representation in the soft-ware industry, a widely recognized concern, requires attracting as well as retaining more women. Hearing from women practitioners, particularly those positioned in multi-cultural settings, about their challenges and and adopting their lived experienced solutions can support the design of programs to resolve the under-representation issue. Goal: We investigated the challenges women face in global software development teams, particularly what motivates women to leave their company; how those challenges might break down according to demographics; and strategies to mitigate the identified challenges. Method: To achieve this goal, we conducted an ex-ploratory case study in Ericsson, a global technology company. We surveyed 94 women and employed mixed-methods to analyze the data. Results: Our findings reveal that women face socio-cultural challenges, including work-life balance issues, benevolent and hos-tile sexism, lack of recognition and peer parity, impostor syndrome, glass ceiling bias effects, the prove-it-again phenomenon, and the maternal wall. The participants of our research provided different suggestions to address/mitigate the reported challenges, including sabbatical policies, flexibility of location and time, parenthood support, soft skills training for managers, equality of payment and opportunities between genders, mentoring and role models to sup-port career growth, directives to hire more women, inclusive groups and events, women's empowerment, and recognition for women's success. The framework of challenges and suggestions can inspire further initiatives both in academia and industry to onboard and retain women. Women represent less than 24% of employees in software development industry and experience various types of prejudice and bias. Even in companies that care about Diversity & Inclusion, “untying the mooring ropes” of socio-cultural problems is hard. Hearing from women, especially those working in a multi-cultural organization, about their challenges and adopting their suggestions can be vital to design programs and resolve the under-representation issue. In this work we work closely with a large software development or-ganization which invests and believes in diversity and inclusion. We listened to women and the challenges they face in global soft-ware development teams of this company and what these women suggest reduce the problems and increase retention. Our research showed that women face work-life balance issues and encounter invisible barriers that prevent them from rising to top positions. They also suffer micro-aggression and sexism, need to show com-petence constantly, be supervised in essential tasks, and receive less work after becoming mothers. Moreover, women miss having more female colleagues, lack self-confidence and recognition. The women from the company suggested sabbatical policies, the flexibil-ity of location and time, parenthood support, soft skills training for managers, equality of opportunities, role models to support career growth, directives to hire more women, support groups, and more interaction between women, inclusive groups and events, women's empowerment by publishing their success stories in media and recognizing their achievements. Our results had been shared with the company Human Resources department and management and they considered the diagnosis helpful and will work on actions to mitigate the challenges that women still perceive. 

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2. Expand Underrepresented Participation in High-Tech Start-Ups.

   Ivanitzki, Teddy ; Johnson Rashida ( February 2023 , 2023 Conference for Industry and Education Collaboration (CIEC))

   CIEC panel (Ed.)

   Abstract: When starting small businesses, particularly in high-tech sectors like artificial intelligence (AI), digital twins, or the Internet of Things (IoT), women and underrepresented minority groups face additional hurdles in securing funding and investment. Not only is such a discrepancy in investment socially unjust, but it deprives the US of the advantages in innovation and global competition that could stem from the widening participation of the underrepresented population in innovative sectors. Although targeted support to women and underrepresented minority-owned businesses is being provided by the federal government and the private sector, more remains to be done to close the investment gap. The US Small Business Administration (SBA, 2013) provides more than $3.5 billion in funding to over 5,000 startups per year through its Small Business Innovation Research (SBIR) and Small Business Technology Transfer (STTR) programs. Moreover, the Small Business Act provides these programs with a mandate to target women and underrepresented minority groups. Despite this mandate from SBA, only 15% of those funds went to minority-owned companies (SBA, 2013). Funding opportunities from the private sector tell a similar story. Diversity VC, a non-profit partnership promoting diversity in Venture Capital, reported in 2019 that in a comprehensive survey (Azevedo, 2019) of around 10,000 founders receiving venture capital backing, only 9% were women and a mere 1% were Black. In order to i) accelerate innovation and increase participation of under-represented minorities in start-ups of “new industry”, and ii) to ensure US competitiveness in the global market, in 2010, the National Science Foundation (NSF) introduced the Small Business Postdoctoral Research Diversity Fellowship (SBPRDF) program and selected the American Society of Engineering Education (ASEE) to administer the program. In recognition of ASEE’s successful performance in meeting the objectives of the SBPRDF program, in 2019 NSF/IIP (Industrial Innovation and Partnerships) program leadership selected ASEE to administer the Innovative Postdoctoral Entrepreneurial Research Fellowship (IPERF) program. The overarching goal of the IPERF program is to emphasize and strengthen the entrepreneurial development of underrepresented Fellows. The IPERF program also aims to advance best practices in postdoctoral programs and impart cross-disciplinary expertise in the application of new technologies like AI and IoT in “new industries” based on bioengineering and biochemistry technologies. 

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3. Women’s Participation in Open Source Software: A Survey of the Literature

   https://doi.org/10.1145/3510460  

   Trinkenreich, Bianca ; Wiese, Igor ; Sarma, Anita ; Gerosa, Marco ; Steinmacher, Igor ( April 2022 , ACM Transactions on Software Engineering and Methodology)

   Women are underrepresented in Open Source Software (OSS) projects, as a result of which, not only do women lose career and skill development opportunities, but the projects themselves suffer from a lack of diversity of perspectives. Practitioners and researchers need to understand more about the phenomenon; however, studies about women in open source are spread across multiple fields, including information systems, software engineering, and social science. This paper systematically maps, aggregates, and synthesizes the state-of-the-art on women’s participation in OSS. It focuses on women contributors’ representation and demographics, how they contribute, their motivations and challenges, and strategies employed by communities to attract and retain women. We identified 51 articles (published between 2000 and 2021) that investigated women’s participation in OSS. We found evidence in these papers about who are the women who contribute, what motivates them to contribute, what types of contributions they make, challenges they face, and strategies proposed to support their participation. According to these studies, only about 5% of projects were reported to have women as core developers, and women authored less than 5% of pull-requests, but had similar or even higher rates of pull request acceptances than men. Women make both code and non-code contributions and their motivations to contribute include, learning new skills, altruism, reciprocity, and kinship. Challenges that women face in OSS are mainly social, including lack of peer parity and non-inclusive communication from a toxic culture. We found ten strategies reported in the literature, which we mapped to the reported challenges. Based on these results, we provide guidelines for future research and practice. 

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4. An AI‑based Approach for Improved Sign Language Recognition using Multiple Videos

   Cameron Dignan, Eliud Perez ( February 2022 , Multimedia tools and applications)

   People with hearing and speaking disabilities face significant hurdles in communication. The knowledge of sign language can help mitigate these hurdles, but most people without disabilities, including relatives, friends, and care providers, cannot understand sign language. The availability of automated tools can allow people with disabilities and those around them to communicate ubiquitously and in a variety of situations with non-signers. There are currently two main approaches for recognizing sign language gestures. The first is a hardware-based approach, involving gloves or other hardware to track hand position and determine gestures. The second is a software-based approach, where a video is taken of the hands and gestures are classified using computer vision techniques. However, some hardware, such as a phone's internal sensor or a device worn on the arm to track muscle data, is less accurate, and wearing them can be cumbersome or uncomfortable. The software-based approach, on the other hand, is dependent on the lighting conditions and on the contrast between the hands and the background. We propose a hybrid approach that takes advantage of low-cost sensory hardware and combines it with a smart sign-recognition algorithm with the goal of developing a more efficient gesture recognition system. The Myo band-based approach using the Support Vector Machine method achieves an accuracy of only 49%. The software-based approach uses the Convolutional Neural Network (CNN) and Recurrent Neural Network (RNN) methods to train the Myo-based module and achieves an accuracy of over 80% in our experiments. Our method combines the two approaches and shows the potential for improvement. Our experiments are done with a dataset of nine gestures generated from multiple videos, each repeated five times for a total of 45 trials for both the software-based and hardware-based modules. Apart from showing the performance of each approach, our results show that with a more improved hardware module, the accuracy of the combined approach can be significantly improved 

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5. U.S. Women Faculty in the Social Sciences Also Face Gender Inequalities

   https://doi.org/10.3389/fpsyg.2022.792756  

   Casad, Bettina J. ; Garasky, Christina E. ; Jancetic, Taylor R. ; Brown, Anne K. ; Franks, Jillian E. ; Bach, Christopher R. ( May 2022 , Frontiers in Psychology)

   There is a national interest in United States women’s underrepresentation in science, technology, engineering, and mathematics (STEM); however, gender inequality in the social sciences has not received similar attention. Although women increasingly earn postgraduate degrees in the social sciences, women faculty still experience gender inequities. Consistent gender inequities include slower career advancement, blunted salaries, unequal workloads, work-life conflict, systemic gender biases, underrepresentation in positions of power, and hostile work environments. Cultural biases suggest that once women have achieved parity, gender bias no longer exists. This review challenges that notion by providing evidence from social science domains in which women are well-represented but continue to face systemic gender biases. We examine cultural influences on gender representation and career advancement in psychology, economics, political science, sociology, and anthropology. We make interdisciplinary comparisons of career trajectories and salaries using national data, documenting patterns across the social sciences. For example, women economists face gendered standards in publishing, and women political scientists are less likely to have their work cited than men. Furthermore, data show that salaries become stagnant as the representation of women in these fields increases. These disparities reflect cultural biases in perceptions of women’s competence stemming from social role theory. We discuss best practices to address these problems, focusing on the ADVANCE organizational change programs funded by the National Science Foundation that target (a) improving academic climate, (b) providing professional development, and (c) fostering social networking. Federally supported interventions can reveal systemic gender biases in academia and reduce gender disparities for women academics in the social sciences. 

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