The Use of Risk Factors Proposed by Developmental Pathways of Antisocial Behaviour in Predicting Program Drop-out
Bibliographic record
Abstract
This archival study investigated the use of risk factors proposed by certain theories of developmental pathways of antisocial behaviour, namely those of Moffitt (1993) and Loeber (1985) , in predicting program drop-out at a treatment facility for youths exhibiting serious behavioural difficulties (Robert/Smart Centre). The study evaluated 113 youths admitted to the RSC on their infractions during treatment and seven risk factors proposed by the two developmental theories. Analyses indicated that youth who failed to complete the RSC prescribed intervention programs exhibited a wider variety of infractions during treatment. Both variety of infractions and program drop-out were significantly predicted by the developmental risk factors. Specifically, infractions, early overt behaviour, current covert behaviour, and cognitive/learning difficulties were the best predictors of program drop-out. Mediation analyses revealed a direct relationship only between program drop-out and current covert behaviour. Interestingly, mediation analyses revealed that variety of infractions suppressed the relationship between program drop-out and cognitive/learning difficulties. The implications of these findings for theory and practice are discussed.
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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 | 0.003 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.004 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".