The connection between child maltreatment and juvenile criminality : within a Canadian context
Bibliographic record
Abstract
Research has repeatedly demonstrated that maltreatment increases the likelihood of criminality when compared to a non-maltreated population. What remains unclear is how maltreatment directly or indirectly affects criminality. This study was conducted to delineate any existing relationships between age of onset, type, severity and chronicity of maltreatment and age of onset, type, severity and chronicity of criminality in a Canadian context. The possible impacts of gender, parental capacity impairments, and reduced child functioning were taken into account when examining this relationship. In addition, the characteristics of these children were examined to see if there were major differences within this group. This retrospective study examined the complete official youth protection and young offender dossiers of 87 subjects, involved with Batshaw Youth and Family Centres, who were maltreated and criminal during the period April 1, 2002 to March 31, 2003. A survey instrument was designed to collect quantifiable data on each child. Findings indicate that maltreated and criminal children are characterized as an extremely high needs population. Within this group, children who came to the attention of DYP in infancy had the highest likelihood of parental and personal functioning issues throughout their lifespan and committed their first official crime at the earliest age. Multiple regressions indicated that parent risk score and age of first known DYP involvement were significant predictors of criminality. These results confirm the important role parents play in determining their child’s life outcomes, and suggest that parenting capacities should be fully evaluated, treatment plans should be comprehensive in nature and based on cognitive abilities of both parent and child, and focus should be placed on permanency planning.
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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.007 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 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".