Aspects of In-Person Audit Tests


The study will be contacted through an audit methodology, which will be comprised of correspondent and in-person tests. These two audit types can capture inequality, discrimination, and biases in the labor market (Portillo et al., 2020; Adamovic, 2020). In-person audit tests involve matching two people in terms of job-linked traits and qualifications but allow them to differ in gender, race, or other elements of interest. Their applications will then be used to evaluate differences in responses from potential employers. Correspondence audits test involve sending applications or resumes of non-real persons to job ads after random allocation of a particular treatment such as race or gender (Guschke & Christensen, 2021; Chamberlain, 2016). Audit tests allow the researcher to have wide control in manipulating the elements of interest and conditions to make the applications suit the study and avoid raising suspicion from the applications. Correspondence audit tests offer convincing data about hiring discrimination since human experience and productivity levels are registered as constant for the candidates involved, but gender is changed. The resume quality is similar, but gender is different; hence call, backs or interview invitations can be attributed to discrimination or unconscious biases (Banaji, 2013; Pavlou, 2021). Audit studies can highly be generalizable because they test discrimination actions in real-life settings.

The current study will investigate white-collar and working-class audit tracks where research will submit different matched pairs of resumes, resumes, and applications for a male and a female to job openings on career ads between June 30 and August 30. The researchers will apply 1600 matched resumes with similar qualified current college graduates to 800 entry-level vacancies for white-collar jobs. For the working class audit track, researchers will apply 1400 matched resumes with similar qualifications for males and females applicants with some skills and experience as well as college degrees to 700 entry-level job openings for the working class. Application submissions will have resume contents with highly similar skills about the specific job opening and ensure only gender or race elements are altered so that qualifications will not be an issue. The researcher will submit a pair of applications with resumes and other requirements to job openings and adverts on different websites.

The tests will be done to a wide audience, including states such as California, Alabama, Texas, and New York. The participants’ locations will not be limited to one area; however, the location may affect the employers’ decisions concerning the candidates’ willingness to relocate to new areas near the workplace (Lundberg & Startz, 1998). By targeting different cities and locations that are offering jobs, the data collection will capture heterogeneous labor markets in places with different unemployment rates.


The selection of occupation will be made with consideration of male-dominated and female-dominated professions with the white-collar as well as working-class audit. The audit on white jobs will test occupations that predominantly need a bachelor’s degree as a minimum requirement and are usually done in offices. The audit on the working class will test occupations that need lower education levels as well as minimal skills. I applied for full-time jobs so all the candidates will have similar work schedules. The occupations selected for the white-collar class are female-dominated jobs such as administrative support and human resource sectors (Cruz, 2016; Perina, 2003). Financial analysts and sales representatives were also selected as white-collar jobs that males dominate. For the working class, I selected female-dominated jobs such as travel agents and office secretaries, then security guards and janitors as male-dominated fields.

Experimental treatment

There will be a gendered name assigned to each application in the cover letter and resume to ensure the employers can easily know the gender of each applicant. The most common names for males and females will be used to reduce the difficulty of discerning applicants’ gender by those who will be checking the resumes (Berrey, 2014). In cases where I wanted to test discrimination on gender, I held race constant by choosing highly common names to avoid aligning to any race. This was assumed that many employers would regard as whites and check on gender alone and other factors. To ensure the race was noticeable by the employers, each pair of resumes intended to test reaction to racial background had a name that suggested being from a non-white background and another suggesting the applicant is white.


The research design has important randomization approaches. For jobs opening, I assigned a male and a female to test gender discrimination or a white’s name or a different race name to test racial bias. The resume quality was similar for each pair to ensure it did not affect the selection for interview and call back, which are mainly positive (Quillian et al. 2020). The submission of resumes was not done separately and not at the same time. Each of the resumes of a pair was submitted within 24 to 48 hours. The 24 to 48 hours were selected to ensure the employers did not close the application duration. The strategy assumed that employers did not suspect any action by the researcher to use resume testing to collect data on discrimination.


The dependent variable is a value indicating whether there was a positive call back from the employer with a yes or no. Independent variables are gender, job type, race, and other factors that may arise during the research.


Adamovic, M. (2020). Analyzing discrimination in recruitment: A guide and best practices for resume studies. International Journal of Selection and Assessment, 28(4), 445-464.

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Chamberlain, R. P. (2016). Five steps toward recognizing and mitigating bias in the interview and the hiring process. Strategic HR Review, 15(5), 199–203.

Cruz, A., (2016). On the Job: White Employers, Workers of Color, and Racial Triangulation Theory. Sociology Compass. 10(10), 918-927.

Guschke, B. L., & Christensen, J. F. (2021). From Individual to Organizational Bias: A Norm-critical Proposition for Unconscious Bias Intervention in Organizations.

Lundberg, S., & Startz, R. (1998). On the Persistence of Racial Inequality. Journal of Labor Economics, 16(2), 292. Web.

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Perina, K. (2003). Race card or resume: Job discrimination. Psychology Today, 36, 12.

Portillo, S., et al. (2020). The Myth of Bureaucratic Neutrality: Institutionalized Inequity in Local Government Hiring. Review of Public Personnel Administration, 40(3), 516-531.

Quillian, LLee, J. J., & Oliver, M. (2020) Evidence from Field Experiments in Hiring Shows Substantial Additional Racial Discrimination after the Callback. Social Forces, 99(2), 732-759.

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