Can we win the “names game”? tactics for large-scale demographic research in entrepreneurship and innovation
本文探讨了在创业与创新研究中，如何利用姓名算法推断性别和种族，以解决人口统计数据缺失的问题，并指出高错误率需结合图像识别来降低，建议优先资助建立人口统计数据库。
Scholars of entrepreneurship and innovation are eager to understand the role of demographics: characterising the representation of women and minorities in publishing, patenting, and startups. Yet progress is hindered by the lack of demographic data in many relevant databases, or the unknown reliability of data fields that are available. Usually knowing little beyond the person’s name, researchers often rely on name algorithms to assign gender and/or race. High error rates can occur from such algorithms unless coupled with image recognition. Providers of public goods should prioritise funding the creation of demographic libraries for scientists, entrepreneurs, and inventors.