Anxious, threatened, and also unethical: How anxiety makes individuals feel threatened and commit unethical acts.
Bibliographic record
Abstract
People often experience anxiety in the workplace. Across 6 studies, we show that anxiety, both induced and measured, can lead to self-interested unethical behavior. In Studies 1 and 2, we find that compared with individuals in a neutral state, anxious individuals are more willing (a) to participate in unethical actions in hypothetical scenarios and (b) to engage in more cheating to make money in situations that require truthful self-reports. In Studies 3 and 4, we explore the psychological mechanism underlying unethical behaviors when experiencing anxiety. We suggest and find that anxiety increases threat perception, which, in turn, results in self-interested unethical behaviors. Study 5 shows that, relative to participants in the neutral condition, anxious individuals find their own unethical actions to be less problematic than similar actions of others. In Study 6, data from subordinate-supervisor dyads demonstrate that experienced anxiety at work is positively related with experienced threat and unethical behavior. We discuss the theoretical and practical implications of our findings.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".