HCC: Small: Human-Centered Computing to Support Citizen Data Science on Gender-based Violence

HCC：小型：以人为中心的计算支持基于性别的暴力的公民数据科学

• 批准号: 2213826
• 负责人: Catherine D'Ignazio
• 金额: $ 59.84万
• 依托单位: Massachusetts Institute of Technology
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-09-01 至 2025-02-28
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2213826&HistoricalAwards=false
• 关键词: HCC; Small; Human; Centered; Computing

This study seeks to better understand citizen data practices, namely, which data are related to serious social problems are more important to citizens and what citizens actually do with open data. It focuses on citizen data about gender-based violence, and specifically data about the killing of women and girls for reasons based on their gender. While there has been a great deal of research on open data, and speculation about its benefits to democracy, there has been comparatively less empirical work. It is well-established that official data on gender violence and feminicide are often incomplete, difficult to access, infrequently updated, and underreported. Citizen groups have stepped into these gendered data gaps. This research project aims to empirically study the informatic practices of groups that undertake citizen data science about feminicide as well as develop design implications for how human-centered computing may better support this work. By systematizing ad-hoc citizen practices into an empirical model and cultivating citizens' own human-centered computing design ideas, this work will advance the practice of citizen data science on the topic of feminicide as well as support public awareness, policy and civil society-public sector collaboration on civic data about gender-based violence.This research will make four contributions to the scholarly literature in the fields of human-computer interaction, critical data studies, women's and gender studies, and sociology. (1) Empirical contribution: The project aims first of all to advance empirical understanding of citizen data science practices about feminicide and gender-based killing which have been the subject of little research. This will provide the empirical groundwork for digital tools and research that can better support citizen data science about gender-based violence, and could potentially lead to increased government-civil society cooperation around feminicide data in the future. (2) Methodological contribution: While research on citizen data practices typically focuses on case studies, this research will undertake a broader and transnational analysis of these practices across a specific topical domain where there is significant citizen energy and activity. (3) Design contribution: By working in an equitable and participatory way with groups themselves, it will contribute high-level design implications for human-centered computing to support citizen data science about gender-based violence, and center the voices and experiences of such groups in the design process. (4) Generalizability of findings: An assessment of fundamental concepts and research methods explored in this research will provide groundwork for equity-oriented citizen data science beyond the domain of gender-based violence.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

这项研究旨在更好地了解公民数据实践，即哪些数据与严重的社会问题有关，对公民来说更重要，以及公民实际上如何使用开放数据。它侧重于关于性别暴力的公民数据，特别是关于因性别原因杀害妇女和女孩的数据。虽然对开放数据进行了大量研究，并对其对民主的好处进行了猜测，但实证工作相对较少。众所周知，关于性别暴力和杀害妇女的官方数据往往不完整、难以获得、不经常更新和报告不足。公民团体已经填补了这些性别数据空白。 该研究项目旨在实证研究从事公民数据科学的团体的信息学实践，以及开发以人为本的计算如何更好地支持这项工作的设计影响。通过将临时公民实践系统化为经验模型，并培养公民自己的以人为本的计算设计理念，这项工作将推动公民数据科学在女性杀戮主题上的实践，并支持公众意识，政策和民间社会-公共部门在关于基于性别的暴力的民间数据方面的合作。这项研究将对人类领域的学术文献做出四项贡献：计算机交互、关键数据研究、妇女和性别研究以及社会学。(1)经验贡献：该项目的目的首先是促进对公民数据科学实践的经验性理解，这些实践涉及杀害妇女和基于性别的杀戮，这是很少研究的主题。这将为数字化工具和研究提供经验基础，可以更好地支持关于性别暴力的公民数据科学，并可能导致政府-民间社会在未来围绕杀害妇女数据加强合作。(2)方法学贡献：虽然对公民数据实践的研究通常侧重于案例研究，但这项研究将对这些实践进行更广泛的跨国分析，这些实践涉及一个具有重要公民能量和活动的特定主题领域。(3)设计贡献：通过以公平和参与的方式与团体合作，它将为以人为本的计算提供高层次的设计影响，以支持有关性别暴力的公民数据科学，并在设计过程中集中这些团体的声音和经验。(4)结论的普遍性：对本研究中探索的基本概念和研究方法进行评估，将为性别暴力领域以外的以公平为导向的公民数据科学奠定基础。该奖项反映了NSF的法定使命，并被认为值得通过使用基金会的知识价值和更广泛的影响审查标准进行评估来支持。