Me?! Never! Social Distance as a Moderator of Other Contextual Factors on Responses to Ethical Scenarios
Bibliographic record
Abstract
ABSTRACT The present research investigates how changes in the extent to which decision‐makers rely on concrete or abstract thinking (i.e., construal level) influence responses to ethical scenarios as well as the relationship between those responses and actual, recalled, unethical behavior. Using 18 different scenarios, across three studies, simultaneous changes in construal level are employed to reveal the importance of social distance—whether the decision‐maker is described as the self or a hypothetical stranger—as a moderator of the effects of other changes in construal level. Study 1 also investigates a potential alternative mechanism, and Study 2 provides evidence for the mediating role of thoughts that are associated with changes in considerations related to the means and activities required to behave unethically and the benefits of behaving unethically. In the final study, self‐reported prior bad behavior is compared to predictions about the same behaviors in order to investigate the role of construal level and social distance on the correlations between predicted and recalled unethical behavior. The article concludes with a brief discussion of the theoretical and practical implications of the present research.
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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 | 0.005 | 0.033 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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 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".