Ambiguous publicities: Cultivating doubt at the intersection of competing genres of risk evaluation in Catalan Prisons
Bibliographic record
Abstract
Policymakers in Canada and across Europe have largely embraced the creation of post-disciplinary systems of punishment. In the autonomous region of Catalonia, Spain, this meant expanding connections between prisons and communities, expanding the publics a prison serves. At the same time, in part driven by austerity policies, incarceration in Spain and Catalonia has become more punitive and bureaucratic. Actuarial risk assessments introduced in Catalan prisons in 2009 are an example of this type of reform—designed to facilitate the release of low-risk inmates earlier and to control mobility. Drawing on ethnographic research conducted in Catalan prisons from 2012 to 2014, I show how both actuarial and clinical risk evaluation involved therapists’ anticipation of future aggressive acts on the part of inmates. Analyzing risk assessment as a practice and as an ideological frame, I argue that the short-term focus of risk assessments reinforced existing forms of interpreting inmates’ actions that therapists attempted to hold at bay. Risk as an ideological frame in the context of austerity contributes to a form of publicity that can further isolate inmates rather than facilitating the construction of community inside and outside of a rehabilitative prison.
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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 | 0.040 | 0.054 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.002 |
| Science and technology studies | 0.017 | 0.070 |
| Scholarly communication | 0.025 | 0.013 |
| Open science | 0.003 | 0.023 |
| Research integrity | 0.004 | 0.008 |
| Insufficient payload (model declined to judge) | 0.003 | 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".