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DOI

10.25035/pad.2019.02.003

Abstract

As the use of technology-mediated interviews (e.g., Skype) is becoming a standard method to interview applicants, it is important to understand how discrimination can still manifest in these types of interviews. Because technology-mediated interviews focus on applicants’ faces, discrimination based on facial stigmas can be particularly inevitable. Thus, the purpose of the current study is to examine how a facial stigma affects visual attention during a technology-mediated interview and acknowledgment as a remediation strategy that individuals might use to reduce the amount of visual attention on a facial stigma. We used a 2 (acknowledge: yes or no) x 2 (target gender: male or female) experimental design. The participants heard a computer-mediated interview while viewing one of the manipulated images. For half of the conditions, the participants heard the applicant acknowledge their stigma. Using an eye tracker, visual attention to the stigma was measured every 30 seconds during the 8-minute interview, producing 16 different time points and a total of 1,792 data points. Multilevel growth curve model analysis examined variation in the trajectory of visual attention to the stigma. The results showed that facial stigmas draw visual attention during a computer-mediated interview, which decreased over time. However, the trajectory of the decrease in visual attention depended on whether an applicant acknowledged their stigma during the interview. The decrease in visual attention was faster in the acknowledgment condition than in the control condition. The current research provides a better understanding to how a facial stigma influences the interview process and provides a theoretical rationale for why acknowledging a facial stigma benefits the interview process.

Reviewer 1 Response.doc (41 kB)
Reviewer 1 Response

Reviewer 2 Response.docx (16 kB)
Reviewer 2 Response

Corresponding Author Information

Juan M. Madera

jmmadera@uh.edu

4450 University Drive, Room 227 Houston, TX 77204

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