A somatic marker perspective of immoral and corrupt behavior
Bibliographic record
Abstract
Individuals who engage in corrupt and immoral behavior are in some ways similar to individuals with psychopathy. Normal people refrain from engaging in such behaviors because they tie together the moral value of society and the risk of punishment when they violate social rules. What is it, then, that allows these immoral individuals to behave in this manner, and in some situations even to prosper? When there is a dysfunction of somatic markers, specific disadvantageous impairments in decision-making arise, as in moral judgment, but, paradoxically, under some circumstances, the damage can cause the patient to make optimal financial investment decisions. Interestingly, individuals with psychopathy, a personality disorder, share many of the same behavioral characteristics seen in VMPFC and amygdala lesion patients, suggesting that defective somatic markers may serve as a neural framework for explaining immoral and corrupt behaviors. While these sociopathic behaviors of sometimes famous and powerful individuals have long been discussed, primarily within the realm of social science and psychology, here we offer a neurocognitive perspective on the possible neural roots of immoral and corrupt behaviors.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.001 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".