The Problem with Templates: Learning from Organic Gang-Related Violence Reduction
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This article considers what demobilisation, disarmament, and reintegration (DDR) programmes might learn from research on gangs and the problems associated with government-instituted ‘wars on gangs’ putatively aimed at reducing or fighting gang-related violence. It begins by considering interventions associated with the global war on gangs, and compares their underlying premises and practices with those of DDR programmes while highlighting how both are plagued with problems associated with drawing on de-contextualized templates. Drawing on long-term ethnographic research carried out in Nicaragua and South Africa, the article then goes on to explore why individuals leave gangs, focusing in particular on the more organic processes that deplete gangs of their members, as well as the consequences that the different possible occupational trajectories of ex-gang members can have for patterns of violence. These offer a number of potential lessons for DDR programmes, particularly with regard to reducing violence in a realistic and sustainable manner.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it