SHF: Small: Retrospective and Prospective Studies of the Effects of Gender Bias in Software Engineering

性别偏见在社会科学领域得到了广泛的研究，但在软件工程方面的研究相对较少，尽管这类问题在技术领域日益突出。2017年，该研究人员发表了一项关于开源领域性别差异和偏见的研究，着眼于开源软件项目的贡献成功率。结果显示，女性接受捐款的可能性高于男性，但当拉取请求者的性别可见时，趋势正好相反。通过增加对降低软件工程中最大的代表性不足群体-女性的排他性的偏见的理解，该项目旨在扩大参与并对社会产生重大好处。该项目将利用一个独特而广泛的数据集，进行关于软件工程中性别偏见的四个家庭的基础研究。第一组研究将使用几种新方法重新检查现有的研究。第二个家族将使用其他平台和其他结果衡量标准对先前的结果进行三角测量。第三个家庭将调查先前文献中发现的偏见的四个方面。第四个研究系列将是隔离偏见影响的实验。这一奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

Gender bias has been researched extensively in the social science community, but relatively little research has been done in software engineering specifically, despite such issues coming to prominence in the technology sphere. In 2017, the investigator published a study on gender differences and bias in open source on a large scale, looking at contribution success rates in open-source software projects. The results showed that the likelihood of a contribution being accepted was higher for women than for men, but the trend is reversed when the gender of the pull requester is visible. By increasing understanding of the biases that decrease exclusivity of women, the largest underrepresented group in software engineering, this project aims to broaden participation and have significant benefits to society.The project will conduct four families of foundational studies about gender bias in software engineering, leveraging a unique and extensive dataset. The first family of studies will re-examine existing studies using several new methods. The second family will triangulate prior results using other platforms and other outcome measures. The third family will investigate four aspects of bias uncovered in prior literature. The fourth family of studies will be experiments that isolate the effect of biases.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.