Organizational Obstacles to Participation in Community Crime Prevention Programs
Bibliographic record
Abstract
The term "organizational obstacles" refers to impediments to participation in community crime prevention groups and activities that stem from program implementation weaknesses. Given the importance that community-based organizations (CBOs) play in mobilizing neighborhoods, these weaknesses can be fatal to collective crime prevention efforts. Based upon research in a poor, high-crime neighborhood in Vancouver, Canada, this article identifies and examines how CBOs may actually inhibit participation in collective crime prevention groups and activities. Program implementation deficiencies that contributed to low participation rates in this neighborhood include weak and ineffectual community outreach and communication, a lack of strong leadership, inadequate resources, a technical and instrumental approach to crime prevention, and the nurturing of a narrow sociodemographic identity of crime prevention program participants that may be exclusionary. The inadequacies of the dominant crime prevention theories and the failure of applied models in promoting a broad-based mobilization of disadvantaged neighborhoods expose the need to develop and apply alternative theories to these unique environments. These alternative theories must pay greater attention to essential collective action processes underlying community crime prevention, emphasizing emotionally based organizing approaches (such as political advocacy, social development, and community development), which may appeal more to the poor and other marginalized groups.
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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 | 0.010 | 0.021 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".