Lying in negotiations: how individual and situational factors influence the use of neutralization strategies
Why this work is in the frame
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Bibliographic record
Abstract
Abstract Lying in negotiations can cause negative emotions, so participants may use neutralization strategies to reduce these feelings. We conducted a 2 (ethical versus non‐ethical climate) × 2 (low versus high negative consequences) experiment to examine how individual and situational factors affect the use of three such strategies: minimizing the lie, denigration of the target, and denial. Lying, psychological distress, and self‐perceived moral attributes were measured as non‐manipulated independent variables. One hundred and ninety‐two MBA students participated in a business negotiation in which they were provided with incentives to lie. As predicted, higher distress was associated with greater denial of lies. In addition, climate and consequences interacted to affect minimization and liars engaged in less minimization than did participants who merely concealed information. Climate and moral attributes interacted to affect denigration. We believe these findings support further study of neutralization strategies in the workplace. Copyright © 2005 John Wiley & Sons, Ltd.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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 it