Using a Bug-Killing Paradigm to Understand How Social Validation and Invalidation Affect the Distress of Killing
Bibliographic record
Abstract
Clinical evidence demonstrates that killing among soldiers at war predicts their experience of long-lasting trauma/distress. Killing leads to distress, in part, due to guilt experienced from violating moral standards. Because social consensus shapes what actions are perceived as moral and just, we hypothesized that social validation for killing would reduce guilt, whereas social invalidation would exacerbate it. To examine this possibility in a laboratory setting, participants were led to kill bugs in an "extermination task." Perceptions of social validation/invalidation were manipulated through the supposed actions of a confederate (Study 1) or numerous previous participants (Study 2) that agreed or refused to kill bugs. Distress measures focused on trauma-related guilt. Higher levels of distress were observed when individuals perceived their actions as invalidated as opposed to when they perceived their actions as socially validated. Implications for posttraumatic stress disorder (PTSD) experienced by soldiers and the paradoxical nature of publicly expressing antiwar sentiments are discussed.
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How this classification was reachedexpand
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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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) | 0.001 | 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 teacher head, 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".