Securing the global city?: an analysis of the ‘Medellín Model’ through participatory research
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 explores the potential contribution to a better understanding and practice of urban security from participatory research methodologies with communities most affected by insecurity and violence. It focusses on the case of Medellín, Colombia, and analyses the key features and impacts of what is known as the ‘Medellín Model’, an approach to urban security widely regarded as innovative and successful. It locates this approach in a history of efforts to reframe security in Latin America, where urban violence has escalated greatly. The shift from ‘security as repression’ to ‘security as management’ has ushered in new models for governing ‘ungoverned’ neighbourhoods. The scrutiny of the effectiveness of these models is limited, however, by the accumulated mistrust and fear in such spaces. This article analyses a methodology for researching security practice on the ground. The paper assesses what difference it makes when academic, civic and social organisations come together to co-produce knowledge with community researchers living in the midst of mutating forms of violence. The methodology, it is argued, enables those most impacted by chronic violence to highlight how insecurity is differentially experienced and to show they can exercise agency in public security policies, making these more relevant and sustainable.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| 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