SBP: A Perfect Match? How Job Demands Shape Gender and Minority Differences in Hiring

职业成就方面的持续地位差异引起了人们的关注，即这种差异是否以及在多大程度上是招聘过程中偏见的结果。这个过程中的一个关键点是，求职者在提交申请后，是否会收到面试或更多信息的回电，以及这种差异是否因社会地位而异。该项目将研究工作要求——与职位空缺相关的所需技能和期望——是否以及如何影响性别和种族在提供回调方面的差异。该项目将研究当工作要求是模糊的还是量化的，女性型的还是男性型的，以及当申请人满足或不满足所需的工作要求时，雇主是否更有可能拒绝女性和少数族裔求职者的回调。该项目还将研究这些模式以及与工作需求的关联如何取决于工作级别和向上与向下的工作流动性。女性和少数族裔面临的偏见代价高昂，不仅对求职者来说是如此，对公司和更广泛的经济来说也是如此，因为它们可能会错过为有才能的人找到合适的工作。通过阐明偏见产生的具体机制和条件，本研究将展示雇主和政府领导人的干预如何减少劳动力市场的不平等。为了研究工作需求如何影响性别和种族不平等程度，以及需求如何与跨工作级别的偏见和向上或向下的工作流动性相关，该项目将开展一项大规模的审计研究。这个实地实验研究将涉及不同的申请人，根据种族和性别，以名字表示。该项目将向在线职位空缺提交大约2万份工作申请，记录回调——面试请求或更多信息——在实验条件下。范围限制在会计、软件工程师、销售人员、人力资源经理等4种职业。每个职业将收到大约5000份工作申请，将申请分为入门级和中级职位，以及处于职业生涯早期和中期阶段的申请人，以代表向上和向下的工作流动性。然后，审计研究中的职位空缺将与在线招聘信息上的专有技能数据相匹配。通过合并这些数据，该项目将识别和描述每个独特职位空缺的工作需求。计算文本分析技术，如主题模型，以及数据集中的信息，将被用来创建变量，根据模糊程度、男性气质或女性气质的关联，以及申请人满足需求的程度，对需求进行分类。使用预测回调的逻辑回归模型，建模与工作需求变量和申请人种族和性别的交互效应。该项目将评估工作需求是否以及如何影响职业和工作水平内的偏见，以及需求是否调解偏见与工作流动性之间的关系。研究结果将为关于劳动力市场运作中的地位差异的社会学理论提供信息，特别是对于专业职业。该奖项反映了美国国家科学基金会的法定使命，并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，被认为值得支持。

Continued status differences in occupational attainment prompt concerns regarding whether and to what extent such differences are a function of bias in the hiring process. A critical point in this process is when job applicants either do or do not receive call backs—request for interviews or more information—after applications have been submitted, and whether such differences vary by social status. This project will examine whether and how job demands – the required skills and expectations associated with a job opening – influence gender and racial differences in offering callbacks. The project will examine whether employers are more or less likely to decline callbacks for women and minority job applicants when the job demands are vague vs. quantified, feminine-typed vs. masculine-typed, and when applicants meet or do not meet the required job demands. The project will additionally examine how such patterns, and the association with job demands, depend on job level and upward vs. downward job mobility. Biases faced by women and minorities are costly, not only to the applicants but to companies and the broader economy that may be missing out on matching talented individuals to appropriate jobs. By elucidating the specific mechanisms and conditions under which biases occurs, this research will demonstrate how interventions by employers and government leaders can reduce inequality in the labor market.To study how job demands affect gender and racial inequality levels, and how demands relate to bias across job level and upward or downward job mobility, the project will field a large-scale audit study. This field experiment study will involve varying applicants by perceived race and gender, signaled by name. The project will submit approximately 20,000 job applications to online job openings, recording callbacks – requests for interviews or more information – across experimental condition. The scope conditions will be limited to four occupations: accountants, software engineers, sales professionals, and human resource managers. Approximately 5,000 job applications will be submitted to each occupation, dividing applications between entry-level and mid-level positions, and between applicants who are in early- or mid-career stages to represent attempts at upward vs. downward job mobility. The job openings in the audit study will then be matched to proprietary skill data on online job postings. By merging these data, the project will identify and characterize the bundle of job demands for each unique job opening. Computational text analysis techniques such as topic models, together with information in the dataset, will be used to create variables to categorize demands by level of vagueness, associations of masculinity or femininity, and the extent to which applicants meet the demands. Logistic regression models predicting callbacks will be used, modeling interaction effects with the job demand variables and applicants’ race and gender. The project will assess whether and how job demands affect bias within occupations and job level, and whether demands mediate the relationship between bias and job mobility. Findings will inform sociological theories regarding status differences in the operation of labor markets, particularly for professional occupations.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.