Adolescent psychopathic traits and adverse environments: Associations with socially adaptive outcomes
Bibliographic record
Abstract
Abstract Researchers have suggested that psychopathic traits among adults may be, at least in part, an adaptive and/or a learned response for securing socially adaptive outcomes in adverse environments, but there is a lack of developmental evidence supporting this hypothesis among adolescents. Therefore, we examined the indirect links from self-perceived adverse environments (parental neglect, socioeconomic status, school competition, neighborhood violence) to evolutionarily relevant social outcomes (social power, dating behavior) through psychopathic traits. A community sample of 396 adolescents completed measures for the study ( M age = 14.64, SD = 1.52). As predicted, there were significant indirect effects from higher levels of parental neglect, school competition, and neighborhood violence to both forms of socially adaptive outcomes through psychopathic traits, but unexpectedly, there were no indirect effects with socioeconomic status. There were also direct effects between environment and socially adaptive outcomes. Results support the hypothesis that psychopathic traits may be, in part, an adaptive and/or learned response to cues from adverse social environments as a means to acquire evolutionarily relevant social outcomes. Interventions could be designed to target the adverse social issues that might be facilitating the development of psychopathy and should be sensitive to the social outcomes adolescents may acquire from these traits.
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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 | 0.000 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".