A latent core of dark traits explains individual differences in peacekeepers’ unethical attitudes and conduct
Why this work is in the frame
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Bibliographic record
Abstract
The influence of military members’ malevolent personality traits on their ethical attitudes and behaviors has been the subject of research for decades. We investigated the relationship between malevolent individual difference factors (Machiavellianism, narcissism, psychopathy, the dominance facet of social dominance orientation, and right-wing authoritarianism) and aspects of military ethics before and during a peacekeeping mission to Mali. Based on pre-service responses from 175 Swedish soldiers, a factor analysis revealed a latent variable to which all individual difference factors contributed. This latent “core of darkness” was related to being more positive toward unethical behaviors both in a warzone and in the Swedish military organization. Extending these findings using a sub-sample of the soldiers (n = 63), we also found that the latent darkness variable prospectively predicted a higher frequency of self-reported insulting and cursing of noncombatants while in Mali. Our results suggest that malevolent individual difference factors have a common core and that moral transgressions during peacekeeping can be predicted and perhaps minimized by identifying soldiers who score high on this common core. However, more research is needed to understand the unique relations of some malevolent factors and different types of morally questionable warzone behavior.
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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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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