Economic Predictors of Differences in Interview Faking Between Countries: Economic Inequality Matters, Not the State of Economy
Why this work is in the frame
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Bibliographic record
Abstract
Many companies recruit employees from different parts of the globe, and faking behavior by potential employees is a ubiquitous phenomenon. It seems that applicants from some countries are more prone to faking compared to others, but the reasons for these differences are largely unexplored. This study relates country‐level economic variables to faking behavior in hiring processes. In a cross‐national study across 20 countries, participants ( N = 3,839) reported their faking behavior in their last job interview. This study used the random response technique (RRT) to ensure participants’ anonymity and to foster honest answers regarding faking behavior. Results indicate that general economic indicators (gross domestic product per capita [GDP] and unemployment rate) show negligible correlations with faking across the countries, whereas economic inequality is positively related to the extent of applicant faking to a substantial extent. These findings imply that people are sensitive to inequality within countries and that inequality relates to faking, because inequality might actuate other psychological processes (e.g., envy) which in turn increase the probability for unethical behavior in many forms.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it