Cultures of transparency in carceral governance: Lessons from the global North/South divide
Bibliographic record
Abstract
This conceptual article offers new ways to map and understand the role of transparency in carceral governance. Mobilizing our expertise in our respective fields of study, we comparatively reflect on case studies of carceral transparency in Argentina, Canada, and Spain. In each, we decentre forms of transparency favoured by carceral authorities by considering the range of mechanisms and actors at play in the production of transparency. Taken together, our accounts of cultures of transparency in prisons and migrant detention facilities in the global north and south highlight absences and presences of different means of generating transparency across carceral sites and denaturalize northern and state-centric ideas about carceral transparency. Ultimately, our juxtaposition of three cultures of transparency reveals the range of means of generating carceral knowledge and the potential scope for its dissemination. Amidst persistent human rights violations, this work underlines the need for further southernized research on transparency to shape possibilities of carceral governance.
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How this classification was reachedexpand
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 | 0.000 | 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 | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".