Bibliographic record
Abstract
Previous research supports the position that more research is needed for understanding the dynamics of co-offending and the promise this will have for effective prevention, policing, rehabilitative and reintegration measures.Previous research also acknowledges that the majority of research has concentrated on youth co-offending.Adult co-offending does plays a significant part in crime and requires further analysis.This exploratory study begins by examining the incidence and importance companions play in criminal behavior and follows with several theoretical positions.Group delinquency is examined generally.Special attention is devoted to leadership in co-offending.Accordingly, leadership measures &om the organizational and social-psychological fields are outlined and twenty empirical studies that measure leadership directly or those that attest measures of leadership are provided.Meta-analysis of these previous studies is conducted to determine what is "known" about leadership in co-offending.Ultimately, it was discovered that studies examining leadership in co-offending are limited by definitional ambiguities in terms of defining co-offending and leadership.Many studies involve low base rates of either participants or case studies and the units of analysis are unclear as to whether those under study consist of dyads, triads or larger units of co-offenders.In addition, the extant literature has focused on specific crimes (i.e.robbery and sexual offences), participants have been largely under the age of 30 years and the methods of data gathering have been limited by focusing on only one of the offenders in the co-offending unit.The implications of these findings are discussed.In light of these findings, an additional statement as to the potential for fbture research on leadership in co-offending and recommendations to policy within the Correctional Service of Canada are offered.Behavior 40 ...
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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 | 0.005 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".