Sports and Tertiary Crime Prevention: Desistance from Crime
Bibliographic record
Abstract
At the tertiary level of crime prevention, the goal of interventions is to prevent recidivism or support desistance from crime. In that context, sport-based programmes either in the community or in a correctional setting are sometimes proposed as a means to contribute to the rehabilitation and reintegration of offenders. However, there are still very few such programmes for young offenders, whether in the community or in institutions. For instance, there was not a single sport-based programme for convicted young offenders among those we reviewed in British Columbia. Despite the fact that sport-based programmes targeting known young offenders remain a rarity and that their crime prevention outcomes have never been properly evaluated, these programmes have nevertheless been declared ‘promising’ (Meek, 2020). Without necessarily disputing that premature conclusion, it is important to realize that the promise in question remains largely theoretical. Some preliminary research has attempted to link sport-based interventions and offenders’ desistance from crime. However, at this point, the effectiveness of rehabilitation efforts through sport remains uncertain (Meek, 2012, 2014, 2018; Meek, Champion, and Klier, 2012; Lewis and Meek, 2012; Gallant, Sherry, and Nicholson, 2015; Meek and Lewis, 2014a, 2014b; Parker, Meek, and Lewis, 2014; Sempé, 2018; Psychou et al, 2019). There are still many unanswered questions around whether these sport-based crime prevention programmes (whether administered in the system or in the community) can aid in desistance from crime and how this process works. Supporting desistance It is important to understand the process of change that tertiary crime prevention programmes are trying to support. That process is perhaps best described as ‘desistance from crime’. The importance of understanding that process is well recognized within criminal career research which tries to account for the onset of, maintenance of, and desistance from criminal behaviour. However, despite its importance to the criminal career paradigm, desistance is relatively understudied in criminology (Lussier, McCuish, and Corrado, 2015). Several desistance studies are relevant to the topic of sports and crime prevention. The best-known among them was Laub and Sampson's (2003) ground-breaking multiple-wave longitudinal study on 500 male delinquents from Boston. The study was based on an impressive dataset that stretched over 40 years, with interviews conducted at various points throughout many of the offenders’ lives.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.010 | 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".