The special prison regime under Article 41bis in Italy. Between detention regime, accessory penalties and prisoner dehumanisation.
Bibliographic record
Abstract
The proposed article deals in detail with the mechanics of the special prison regime of maximum restriction applied in Italy. This regime is not dissimilar from its counterparts in various prison systems, which may sometimes be more rigid and restrictive in their normative prediction, and at other times more so in their concrete application. If the quality of a democracy is measured by the quality of life in its prisons, to deal with it, especially in regimes of specific fragility of prison life (juvenile prisons, special restriction regimes, psychiatric prisons), is to deal with the civilisation of a country. Psychologists can - and must - do a great deal in this critical and concrete analysis, especially in highlighting the psychologically critical aspects of deprivation regimes. Article 41bis of the Italian Prison Ordinance Law has raised numerous and penetrating constitutionality issues over the years, almost all of them centred on the substantial conflict of the prison legislation with Article 27 paragraph 3 of the Constitution. In addition to a brief examination of the article in question, we will discuss its application, which poses quite a few critical elements in terms of the dehumanisation of the prisoner and the overall system envisaged.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.010 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.006 | 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".