We are conducting a meta-analysis on evaluations and decision-making in technology-mediated employment interviews and are seeking both published and unpublished studies. Specifically, we are interested in research examining how evaluations in such interviews (e.g., asynchronous or synchronous video interviews, virtual reality interviews, telephone interviews) are influenced by socio-demographic or other applicant characteristics (e.g., gender, age, race, social or economic status, language, sexuality, political views, attractiveness, tattoos) rather than the actual interview content (e.g., response quality). Our goal is to understand the extent to which factors other than interview content affect evaluative judgments. We include data collected during or after 2020.
We particularly welcome unpublished manuscripts, dissertations, theses, conference papers, or raw data that explore bias or decision-making processes in technology-mediated employment interviews but may not be easily found through journal searches. If you know of relevant published work meeting these criteria, please feel free to share it as well.
If you are willing to share your study or data, we would appreciate any of the following: Descriptive statistics of dependent variables (means, standard deviations, sample sizes) by condition, details on measures (e.g., reliability estimates, item sources), description of how socio-demographic factors were manipulated or operationalized, study context (e.g., real vs. mock job applications, job type or organization), sample characteristics and study design (e.g., between- vs. within-subjects), and preferred citation format.
Please send materials or study details to julia.buettner@uni-ulm.de. Data will be treated confidentially and not shared beyond our research team without permission.
Deadline: December 31, 2025
Post Type
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