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Limited interaction with professionals, infrastructural, and social constraints put barriers in providing holistic support to expectant and new mothers in low-resource settings. We examine the use of digital support groups facilitated through WhatsApp by a non-government organization in India. Complementing prior research, these digital peer support groups inform about an open public space created over a chat platform where rural communities and health professionals can engage. By qualitatively analyzing six months of interaction among 588 group members and collecting the experiences of the group moderators, we inform about how the support groups acted as an important source for compensating the gaps in the existing healthcare, providing reassurance support on routine health, explanation on test reports, validation and counseling support in ongoing treatments. We also derive implications for the future of digital support groups and the need for further research on the use of unplatformed design models in resource-constrained settings.
China has witnessed rapid growth in their e-commerce markets and livestreaming communities in recent years. The commercialization of livestreaming has led to the rise of e-commerce livestreamers, among which rural women constitute a substantial portion. To understand the motivations underlying these women’s choices to engage in livestreaming activities and probe the extent to which they are empowered by this new form of entrepreneurship, we conducted an interview-based study with rural female livestreamers. We found that these women chose to be livestreamers for practical and self-presentation purposes and they gained a sense of self-empowerment through economic, social, intellectual, psychological, and spiritual dimensions. At the same time, however, they experienced and confronted social stigmas rooted in rural societies and the strategies they used to deal with these biases were vastly different. Our work contributes to the HCI community by providing a nuanced understanding of the motives and lived experiences of rural female livestreamers and provides design implications that could improve the everyday experiences of these livestreamers.
Women's economic empowerment is central to gender equality. However, work opportunities available to low-income women in patriarchal societies are infrequent. While crowd work has the potential to increase labor participation of such women, much remains unknown about their engagement with crowd work and the resultant opportunities and tensions. To fill this gap, we critically examined the adoption and use of a crowd work platform by low-income women in India. Through a qualitative study, we found that women faced tremendous challenges, for example, in seeking permission from family members to do crowd work, lack of family support and encouragement, and often working in unfavorable environments where they had to hide their work lives. While crowd work took a toll on their physical and emotional wellbeing, it also led to increased confidence, agency, and autonomy. We discuss ways to reduce frictions and tensions in participation of low-income women on crowd work platforms.
Automatic Speech Recognition (ASR) researchers are turning their attention towards supporting low-resource languages, such as isiXhosa or Marathi, with only limited training resources. We report and reflect on collaborative research across ASR & HCI to situate ASR-enabled technologies to suit the needs and functions of two communities of low-resource language speakers, on the outskirts of Cape Town, South Africa and in Mumbai, India. We build on longstanding community partnerships and draw on linguistics, media studies and HCI scholarship to guide our research. We demonstrate diverse design methods to: remotely engage participants; collect speech data to test ASR models; and ultimately field-test models with users. Reflecting on the research, we identify opportunities, challenges, and use-cases of ASR, in particular to support pervasive use of WhatsApp voice messaging. Finally, we uncover implications for collaborations across ASR & HCI that advance important discussions at CHI surrounding data, ethics, and AI.