La prison au travers de l’espace architectural
Bibliographic record
Abstract
Le numéro vise à éclairer l’enfermement à partir de l’espace architectural pour analyser des interactions, des pratiques, des gestes, et des expériences dans divers lieux de détention. Il s’agit de proposer une vision critique, non programmative et non normative, des espaces architecturaux de détention ; soit, de comprendre comment ils sont produits et ce qu’ils produisent. Ce numéro propose ainsi des regards pluridisciplinaires sur des lieux spécifiques de l’enfermement, pour appréhender la multiplicité de l'espace architectural : de la programmation gouvernementale en matière d’architecture carcérale aux pratiques réelles de circulations en détention, de l’histoire de la cellule en France aux enjeux de l'intimité dans des prisons canadiennes, de l’essor de prisons-modèles en Espagne aux interrelations fines en Centre éducatif fermé en France, en passant par la répartition des individus en prison. Les textes sont empiriquement riches, rendant honneur à la singularité des lieux qu’ils visitent, tout en éclairant plusieurs enjeux de l’enfermement contemporain. Ils sont tirés d’une série de séminaires financés par le Groupement européen de recherches sur les normativités (GERN) CNRS : https://www.gern-cnrs.com/. The issue aims to examine confinement through architectural space in order to analyse interactions, practices, gestures, and experiences in different places of detention. The objective is to propose a critical, non-programmatic and non-normative vision of detention architectural spaces; that is, to understand how they are produced and what they produce. This issue thus offers multidisciplinary perspectives on specific places of confinement: to grasp the multiplicity of architectural space from government programming in terms of prison architecture to actual practices of circulation in detention, from the history of the cell to the issue of privacy in Canadian prisons, from the rise of model prisons in Spain to the interrelationships in “closed educational centres” in France, and including the distribution of individuals in prison. The texts offer a rich empirical perspective, honouring for the singularity of the places they visit, while shedding light on several issues of contemporary imprisonment. They are drawn from a series of seminars funded by the Groupement européen de recherches sur les normativités (GERN) CNRS: https://www.gern-cnrs.com/.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.019 |
| Scholarly communication | 0.008 | 0.006 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.015 | 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".