A profile of youth and young adults with criminal offences
Bibliographic record
Abstract
Youth with corrections involvement often have complex needs that would benefit from coordination between service providers. This report used administrative data to profile youth (12 to 25 years old) that had criminal offences between 2005/06 and 2010/11. Analyses examined these individuals’ sociodemographic characteristics and public service use patterns based on their total number of offences and offence type(s). This report found that (1) around 3% of youth and young adults in Alberta had criminal offences in a given year (22,415 to 25,135 a year from 2005/06 to 2010/11), (2) the proportion of both female offenders and offenders meeting or exceeding educational expectations increased over time, (3) the most common types of offences were administrative and property, followed by violent and other criminal, (4) youth with administrative offences were the least likely of the types of offenders to be meeting or above educational expectations, and (5) drug offenders made up the lowest percentage of total offences and have different sociodemographic characteristics and public service use patterns than other offender types. These findings provide policy-relevant evidence that public authorities may consider as they seek to better support young adult offenders.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".