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

SBP：完美匹配？

• 批准号: 1948237
• 负责人: Katherine Weisshaar
• 金额: $ 26.75万
• 依托单位: University of North Carolina at Chapel Hill
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-03-01 至 2023-02-28
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1948237&HistoricalAwards=false
• 关键词: SBP; Perfect; Match; How; Job

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.

职业成就方面持续存在的地位差异促使人们关注这种差异是否以及在多大程度上是招聘过程中的偏见。 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回电要求面试或更多信息，以及这种差异是否因社会地位而异。 这个项目将研究工作要求-所需的技能和期望与一个职位空缺-是否以及如何影响性别和种族差异提供回调。该项目将研究当工作要求模糊与量化、女性型与男性型以及申请人满足或不满足所需的工作要求时，雇主是否更有可能或更少地拒绝对女性和少数族裔工作申请人的回电。该项目还将研究这种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。 女性和少数族裔面临的偏见不仅对申请人，而且对公司和更广泛的经济来说都是代价高昂的，因为这些公司和经济可能会错过将有才华的个人与合适的工作相匹配的机会。本研究通过阐明偏见产生的具体机制和条件，说明雇主和政府领导者的干预如何减少劳动力市场的不平等。为了研究工作要求如何影响性别和种族不平等程度，以及工作要求与不同职位的偏见和向上或向下的工作流动性之间的关系，本项目将进行大规模的审计研究。这项实地实验研究将涉及不同的申请人感知的种族和性别，通过名字的信号。该项目将向在线职位空缺提交大约20，000份工作申请，并在实验条件下记录回调-面试或更多信息的请求。范围条件将限于四种职业：会计师、软件工程师、销售专业人员和人力资源经理。每个职业将提交大约5 000份工作申请，将申请分为初级和中级职位，以及处于职业生涯早期或中期的申请人，以代表向上和向下的工作流动。审计研究中的职位空缺将与网上职位公告中的专有技能数据相匹配。通过合并这些数据，该项目将确定每个独特职位空缺的一揽子职位需求并说明其特点。计算文本分析技术，如主题模型，连同数据集中的信息，将被用来创建变量，以分类的要求，按水平的熟练程度，男性或女性的协会，以及申请人满足要求的程度。逻辑回归模型预测回调将被使用，建模与工作需求变量和申请人的种族和性别的相互作用的影响。 该项目将评估工作需求是否以及如何影响职业和工作级别内的偏见，以及需求是否调解偏见和工作流动性之间的关系。调查结果将告知社会学理论的地位差异，在劳动力市场的运作，特别是对专业职业。这个奖项反映了NSF的法定使命，并已被认为是值得支持，通过评估使用基金会的智力价值和更广泛的影响审查标准。