Workshop on Gender and Diversity Analysis in Research across the Science Infrastructure

在研究设计和分析中融入关于生物和社会类别交叉和重叠方式的新观点，导致了许多学科的发现和创新。它还促进严谨、可复制和负责任的科学和技术。例如，汽车安全系统得到了极大的改进，以增加对女性的伤害保护，因为国家车祸数据是男女司机分开的，女性车祸假人被引入来解释加速度对性别生物力学的影响。为了从这种方法在科学和工程研究中提供的视角中获益，学术研究基础设施的三大支柱必须协调努力。该项目将大学的研究人员和管理人员、期刊编辑和资助机构聚集在两个国际研讨会上。 这两个研讨会将分享美国和加拿大社区的观点和资源，旨在促进计算机科学和工程研究中的iSGDA。 近年来，将交叉性、性别和多样性分析（iSGDA）纳入医学、健康和生命科学研究取得了很大进展。 这些讲习班将借鉴这些模式，重点关注落后的领域。 与会者将包括来自计算机科学和工程各个领域的研究人员，包括人工智能，机器学习，机器人技术，自然语言处理，机械，土木和其他工程。研讨会的长期目标是：概念化将iSGDA纳入研究设计，流程，分析和研究结果解释的方法;向研究机构，资助机构和同行评审期刊的研究人员和工作人员传播方法;培训当前和下一代的研究人员，他们担任资助机构，期刊，招聘，任期和晋升委员会的同行评审员，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智力价值和更广泛的影响审查标准进行评估来支持。

Integrating into research design and analysis new perspectives on the ways in which biological and social categories intersect and overlap has led to discovery and innovation across numerous disciplines. It also promotes rigorous, reproducible and responsible science and technology. For example, car safety systems were dramatically improved to increase injury protection for women after national car crash data were separated for male and female drivers and female car crash dummies were introduced to account for the effect of acceleration on sex-specific biomechanics. To reap the benefits of the perspectives this approach offers in science and engineering research, it is essential that three pillars of academic research infrastructure coordinate efforts. This project brings together researchers and administrators at universities, journal editors, and funding agencies in two international workshops. The pair of workshops will share perspectives and resources across the U.S. and Canadian communities with the aim of fostering iSGDA in computer science and engineering research. Much progress has been made recently incorporating intersectional sex, gender, and diversity analysis (iSGDA) into medicine, health, and life science research. The workshops will draw from those models where relevant and focus on fields that are lagging behind. Attendees will include researchers from all areas of computer science and engineering, including artificial intelligence, machine learning, robotics, natural language processing, mechanical, civil, and other engineering. The long-term goals of the workshops are to: conceptualize methodologies for integrating iSGDA into research design, processes, analysis, and interpretation of research results; disseminate methods to researchers and staff across research institutions, funding agencies, and peer-reviewed journals; train the current and next generation of researchers who serve as peer reviewers for funding agencies, journals, and hiring, tenure, and promotion committees, and train faculty on best practices for incorporating these methods into core courses in their disciplines.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.