The convert, the remorseful and the rescued: Three different processes of desistance from crime
Bibliographic record
Abstract
One of the key issues in research on criminal desistance is the impossibility of stating with any degree of certainty that an offender's criminal career is in fact over. When no clear demarcation line can be established for the precise moment when criminal activity has ended, researchers instead distinguish between the cessation of criminal behaviour and the process of desistance. A second issue lies in the contradictions inherent in explanatory theories on desistance that focus either on agents or, conversely, on the structures that provoke and support the process of change. An integrative theoretical framework on criminal desistance, influenced by the work of Margaret Archer (1995 , 2000 , 2002) and showing the interplay between structures and agents, can be found elsewhere (F.-Dufour, Brassard, and Martel, forthcoming). The application of this framework to empirical data collected from 29 Canadian offenders serving conditional sentences reveals the existence of three distinct processes leading to desistance among those we metaphorically call the transformed, the remorseful and the rescued.
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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 | 0.002 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.005 | 0.019 |
| Scholarly communication | 0.011 | 0.007 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 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".