Investigating impression management use in asynchronous video interviews across 10 countries
Bibliographic record
Abstract
Abstract This cross‐cultural study investigates how interviewees from 10 culturally‐distinct countries differ in their use of impression management (IM) tactics in asynchronous video interviews (AVIs), and the relationship(s) between those tactics and interview performance. A total of 582 participants from ten countries (India, Canada, South Africa, Poland, Spain, Iran, Germany, Chile, Philippines, China) completed an 8‐question AVI for a mock position as a manager in a bank. We drew upon GLOBE's cultural framework to predict and explain observed differences in self‐reported IM use and performance. We used multi‐level modeling to test our hypotheses. Interviewees from our ten countries differed slightly in their IM use for various tactics, but IM use was seldom related to GLOBE cultural dimensions. Partially consistent with previous in‐person interview research, honest IM tactics (e.g., self promotion) were positively, but deceptive tactics (e.g., extensive image creation) negatively, associated with interview performance. This research is the first to investigate cross‐cultural IM differences in AVIs, thus addressing a critical gap in the selection literature at a time when many organizations conduct interviews virtually to save costs, streamline the hiring process, or simply conduct most of their activities remotely.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".