Theory of Change Underlying Sport-Based Programmes
Bibliographic record
Abstract
As discussed in previous chapters, the relationship between sport and crime has been difficult to disentangle. Some argue that involvement with sport results in a variety of positive impacts for youth including increases in resiliency, selfesteem, self-efficacy, and a wider network of relationships and opportunities (Morgan and Costas Batlle, 2019; Morgan, Parker, and Roberts, 2019; Morgan et al, 2019). Others have noted that there is a link between sport participation and involvement in certain types of delinquency including violence and problematic alcohol use (Stansfield, 2017). It is very clear that involvement in sport can impact different aspects of one's personality and social setting in both positive and negative ways. It is also quite clear that risk-based theories of youth crime prevention rest on shaky evidence and that youth development interventions, through sports or other forms of interventions, must demonstrate how they can produce tangible crime prevention outcomes. According to a recent UNODC desk review (Samuel, 2018), sport-based crime prevention programmes with welldeveloped methodologies and robust theories of change are the exception rather than the rule. Most programmes fall into the category of local grassroots initiatives, often established by youth for youth, with limited resources and capacity, with only broad identifiable goals, and with no clearly identifiable methodologies or documented assessments of their effectiveness (Samuel, 2018: 62). There have been several attempts to develop a theory of positive development through sports (Coalter, 2013a; Noble and Coleman, 2016; Holt et al, 2017) and at least one attempt to propose a theoretical framework that links sports to positive youth development (PYD) and crime prevention (Morgan et al, 2019). Despite substantial research progress in the last decade, there is a lack of a clear and coherent theoretical conception of these sport-based prevention programmes, an understanding of how and why they might be expected to work, and, therefore, how they can most effectively be implemented. This chapter presents an attempt to conceptualize the links between criminological theory and sport-based crime prevention programmes. This is a prerequisite to forming a cogent theory to explain how sport-based programmes can, at least theoretically, produce crime prevention outcomes at the individual level. This involves clarifying existing concepts and connecting them to existing theories commonly used to understand youth offending and desistance from crime.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.011 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.018 | 0.002 |
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".