THE CRACOW INSTRUMENT FOR MULTI-PROBLEM VIOLENT YOUTH: EXAMINING THE POSTDICTIVE VALIDITY WITH A SAMPLE OF PRESCHOOLERS
Bibliographic record
Abstract
<p>The Cracow is an assessment tool used to identify the risk/need factors in youth at various developmental stages, with the goal of developing individual, familial, and community interventions for violent youth. The Cracow is comprised of three sections measuring the risk/needs of the youth, treatment and intervention options, and externalizing behaviours. The current postdictive validity study of the first section of the Cracow examines the extent to which risk/need factors identify the most physically aggressive preschoolers. The study is based on the first 100 children (boys, <em>n </em>= 58; girls, <em>n</em> = 42) recruited as part of the Vancouver Longitudinal Study on the Psychosocial Development of Children conducted in Vancouver, British Columbia, Canada. A series of latent class analyses (LCA) suggests the presence of three groups of physically aggressive children: a low-, medium-, and high-level group. Subsequent analyses suggest that children in the highly physically aggressive profile were more likely to have risk/need factors in the following five domains: (a) pre/perinatal, (b) socio-economic, (c) family environment, (d) child psychological functioning, and (e) parenting. Findings are discussed in light of the scientific literature on the early prevention of antisocial and aggressive behaviour.</p>
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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 | 0.004 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".