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1. Leveraging mobile phones to attain sustainable development

   https://doi.org/10.1073/pnas.1909326117  

   Rotondi, Valentina; Kashyap, Ridhi; Pesando, Luca Maria; Spinelli, Simone; Billari, Francesco C. (June 2020, Proceedings of the National Academy of Sciences)

   null (Ed.)

   For billions of people across the globe, mobile phones enable relatively cheap and effective communication, as well as access to information and vital services on health, education, society, and the economy. Drawing on context-specific evidence on the effects of the digital revolution, this study provides empirical support for the idea that mobile phones are a vehicle for sustainable development at the global scale. It does so by assembling a wealth of publicly available macro- and individual-level data, exploring a wide range of demographic and social development outcomes, and leveraging a combination of methodological approaches. Macro-level analyses covering 200+ countries reveal that mobile-phone access is associated with lower gender inequality, higher contraceptive uptake, and lower maternal and child mortality. Individual-level analyses of survey data from sub-Saharan Africa, linked with detailed geospatial information, further show that women who own a mobile phone are better informed about sexual and reproductive health services and empowered to make independent decisions. Payoffs are larger among the least-developed countries and among the most disadvantaged micro-level clusters. Overall, our findings suggest that boosting mobile-phone access and coverage and closing digital divides, particularly among women, can be powerful tools to attain empowerment-related sustainable development goals, in an ultimate effort to enhance population health and well-being and reduce poverty. 

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2. Modeling Women's Elective Choices in Computing

   https://doi.org/10.1145/3623762.3633497  

   Bradley, Steven; Parker, Miranda C; Altin, Rukiye; Barker, Lecia; Hooshangi, Sara; Kunkeler, Thom; Lennon, Ruth G; McNeill, Fiona; Minguillón, Julià; Parkinson, Jack; et al (December 2023, ACM)

   Evidence-based strategies suggest ways to reduce the gender gap in computing. For example, elective classes are valuable in enabling students to choose in which directions to expand their computing knowledge in areas aligned with their interests. The availability of electives of interest may also make computing programs of study more meaningful to women. However, research on which elective computing topics are more appealing to women is often class or institution specific. In this study, we investigate differences in en- rollment within undergraduate-level elective classes in computing to study differences between women and men. The study combined data from nine institutions from both Western Europe and North America and included 272 different classes with 49,710 student enrollments. These classes were encoded using ACM curriculum guidelines and combined with the enrollment data to build a hier- archical statistical model of factors affecting student choice. Our model shows which elective topics are less popular with all students (including fundamentals of programming languages and parallel and distributed computing), and which elective topics are more pop- ular with women students (including mathematical and statistical foundations, human computer interaction and society, ethics, and professionalism). Understanding which classes appeal to different students can help departments gain insight of student choices and develop programs accordingly. Additionally, these choices can also help departments explore whether some students are less likely to choose certain classes than others, indicating potential barriers to participation in computing. 

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3. Women's Perspectives on Harm and Justice after Online Harassment

   https://doi.org/10.1145/3555775  

   Im, Jane; Schoenebeck, Sarita; Iriarte, Marilyn; Grill, Gabriel; Wilkinson, Daricia; Batool, Amna; Alharbi, Rahaf; Funwie, Audrey; Gankhuu, Tergel; Gilbert, Eric; et al (November 2022, Proceedings of the ACM on Human-Computer Interaction)

   Social media platforms aspire to create online experiences where users can participate safely and equitably. However, women around the world experience widespread online harassment, including insults, stalking, aggression, threats, and non-consensual sharing of sexual photos. This article describes women's perceptions of harm associated with online harassment and preferred platform responses to that harm. We conducted a survey in 14 geographic regions around the world (N = 3,993), focusing on regions whose perspectives have been insufficiently elevated in social media governance decisions (e.g. Mongolia, Cameroon). Results show that, on average, women perceive greater harm associated with online harassment than men, especially for non-consensual image sharing. Women also prefer most platform responses compared to men, especially removing content and banning users; however, women are less favorable towards payment as a response. Addressing global gender-based violence online requires understanding how women experience online harms and how they wish for it to be addressed. This is especially important given that the people who build and govern technology are not typically those who are most likely to experience online harms. 

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4. Autosegmental Neural Nets: Should Phones and Tones be Synchronous or Asynchronous?

   https://doi.org/10.21437/Interspeech.2020-1834  

   Li, Jialu; Hasegawa-Johnson, Mark (October 2020, Interspeech)

   null (Ed.)

   Phones, the segmental units of the International Phonetic Al-phabet (IPA), are used for lexical distinctions in most human languages; Tones, the suprasegmental units of the IPA,are used in perhaps 70%. Many previous studies have explored cross-lingual adaptation of automatic speech recognition(ASR) phone models, but few have explored the multilingual and cross-lingual transfer of synchronization between phones and tones. In this paper, we test four Connectionist Temporal Classification (CTC)-based acoustic models, differing in the degree of synchrony they impose between phones and tones.Models are trained and tested multilingually in three languages,then adapted and tested cross-lingually in a fourth. Both synchronous and asynchronous models are effective in both multi-lingual and cross-lingual settings. Synchronous models achieve lower error rate in the joint phone+tone tier, but asynchronous training results in lower tone error rate. 

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5. Women's employment and fertility in a global perspective (1960–2015)

   https://doi.org/10.4054/DemRes.2020.43.25  

   Behrman, Julia; Gonalons-Pons, Pilar (July 2020, Demographic Research)

   null (Ed.)