Intellectual Quotient and Social Cognition in Young Offenders: A Relational Analysis
Bibliographic record
Abstract
Antisocial personality disorder (ASPD) showed a broad executive function, as well as visual short-term, working memory (WM), and attention deficits. The inhibitory control and WM deficits may distinguish ASPD from other personality disorders. People with ASPD structure have deficiencies in the maturation of the prefrontal cortex which is evident in various neurocognitive problems, mainly in WM and social cognition (SC). In Colombia there is a high incidence of ASPD in young offenders, which makes the process of rehabilitation and resocialization more difficult. The aim of this paper was to develop a structural equation model (SEM) to identify the relationship between SC and intellectual quotient (IQ) in offenders with ASPD and make a comparative analysis by gender. A representative sample of 120 offenders was used (60 men and 60 women) of a Specialized Attention Center (SAC) in Medellin, Colombia. This paper concludes that there is a higher correlation between SC and IQ in women offenders with ASPD (σxy = 0.62) than in male offenders with ASPD (σxy = 0.54). Epidemiologists suggest that women have a high prevalence of depressive and anxiety disorders, which can be explained by internalized behavioral management. In general, men show a higher prevalence of disorders associated with impulse control through externalizing behavioral management. This shows that ASPD has been studied more in men and that ASPD profiles in women are lacking due to its low prevalence. Based on the results of the model developed, a neurocognitive profile of men and women with ASPD is presented.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".