Bibliographic record
Abstract
This article examines the role of co‐offending in the development of the delinquent career. Hypotheses derived from Reiss's (1986, 1988) taxonomic theory of co‐offending are tested, using police‐reported data on the delinquent careers and co‐offending of 55,336 Canadian offenders. Support is found for a taxonomic theory and for age‐related and functional theories of co‐offending. The taxonomy consists of two types of offenders—high activity (3 percent) and low activity (97 percent)—whose co‐offending patterns differ during the teenage years but not during childhood. For low‐activity offenders as teenagers, the proportion of co‐offenses decreases with criminal experience. The rate of co‐offending by high‐activity offenders as teenagers is lower at onset than for low‐activity offenders, and it varies little with criminal experience. For both offender types, the proportion of co‐offenses decreases with age, is slightly less in males, and varies with the type of offense. For both offender types, the proportion of co‐offenses in childhood offending is greater than in the teenage years and is unrelated to the offender's age or criminal experience.
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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 | 0.001 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 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".