Unintended Consequences of Interview Faking: Impact on Perceived Fit and Affective Outcomes
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Drawing on signalling theory, we propose that use of deceptive impression management (IM) in the employment interview could produce false signals, and individuals hired based on such signals may incur consequences once they are on the job—such as poor perceived fit. We surveyed job applicants who recently interviewed and received a job to investigate the relationship between use of deceptive IM in the interview and subsequent perceived personjob and person-organization fit, stress, well-being, and employee engagement. In a twophase study, 206 job applicants self-reported their use of deceptive IM in their interviews at Time 1, and their perceived person–job and person–organization fit, job stress, affective well-being, and employee engagement at Time 2. Deceptive IM had a negative relationship with perceived person–job and person–organization fit. As well, perceived fit accounted for the relationship between deceptive IM and well-being, employee engagement, and job stress. The findings indicate that using deceptive IM in the interview may come at a cost to employees.
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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 | 0.000 | 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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 it