Bibliographic record
Abstract
OBJECTIVE: To review published works on the epidemiology, risk factors, protective factors, typologies, and genetic aspects of conduct disorder (CD). METHOD: Findings from refereed journal articles and current texts in the field are briefly summarized. RESULTS: CD is commonly encountered in clinical practice. Factors strongly predictive of future delinquency include past offenses, antisocial peers, impoverished social ties, early substance use, male sex, and antisocial parents. Factors that moderately predict recidivism include early aggression, low socioeconomic status (SES), psychological variables such as risk taking and impulsivity, poor parent-child relationships, poor academic performance, early medical insult, and neuropsychological variables such as poor verbal IQ. Mildly predictive variables include other family characteristics such as large family size, family stress, discord, broken home, and abusive parenting, particularly neglect. Protective factors include individual factors such as skill competence (in social and other arenas), adult relationships, prosocial and proeducational values, and strong social programs and supports. CONCLUSIONS: We know a great deal about psychosocial risk factors for CD. Some research into protective factors and genetic contributions exists but is in its early stages. Future work will increase our knowledge about subtypes, developmental pathways, and CD treatment.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".