The Garrison and the Jamaican State: A Model for Co-optation
Bibliographic record
Abstract
The informal system that is present in communities called garrisons in Jamaica often operate outside of the law. Under the leadership of dons, who were initially appointed to carry out the dictates of politicians, the operations of the garrison accounts for approximately 40% of Jamaica’s homicide and is perceived as a socially disorganized space. Research done on these communities suggests that dismantling these communities will ameliorate the high incidence of crime. The main question of this study is, are these communities socially disorganized spaces? The major argument is, the ineptitude of the Jamaican state has resulted in the institution of various mechanisms by non-state actors within these communities to address their justice concerns, and there is an implicit reliance on their services by the Jamaican state. The problem of crime in Jamaica is complex and requires a multi-dimensional approach to addressing the issue. In this paper, I use a Foucauldian lens to highlight the utility of this instituted informal system and suggest that any strategies geared towards addressing crime and violence that occur in these communities should explore coalescing these informal structures into Jamaica’s formal framework.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.019 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.011 | 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".