Minor Physical Anomalies and Family Adversity as Risk Factors for Violent Delinquency in Adolescence
Bibliographic record
Abstract
OBJECTIVE: Minor physical anomalies are considered indicators of disruption in fetal development. They have been found to predict behavioral problems and psychiatric disorders. This study examined the extent to which minor physical anomalies, family adversity, and their interaction predict violent and nonviolent delinquency in adolescence. METHOD: Minor physical anomalies were assessed in a group of 170 adolescent boys from low socioeconomic status neighborhoods of Montréal. The boys had been enrolled in a longitudinal study since their kindergarten year, when an assessment of family adversity had been made on the basis of familial status and the parents' occupational prestige, age at the birth of the first child, and educational level. Adolescent delinquency was measured by using self-reported questionnaires and a search of official crime records. RESULTS: Results from logistic regression analyses indicated that both the total count of minor physical anomalies and the total count of minor physical anomalies of the mouth were significantly associated with an increased risk of violent delinquency in adolescence, beyond the effects of childhood physical aggression and family adversity. Similar findings were not found for nonviolent delinquency. CONCLUSIONS: Children with a higher count of minor physical anomalies, and especially a higher count of anomalies of the mouth, could be more difficult to socialize for different and additive reasons: they may have neurological deficits, and they may have feeding problems in the first months after birth. Longitudinal studies of infants with minor physical anomalies of the mouth are needed to understand the process by which they fail to learn to inhibit physical aggression.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".