Communicating Censure: The Relevance of Conditions of Imprisonment at Sentencing and During the Administration of the Sentence
Bibliographic record
Abstract
In common law, sentencing is chiefly concerned with the duration of a sentence and rarely engages in the conditions under which the sentence is served. Recently, courts in Canada and England and Wales have started to recognise the relevance of certain prison conditions when deciding sentences. These approaches, however, have lacked conceptual clarity and consistency. Building on communicative theories of punishment, this article proposes a novel framework based on ‘state responsibility/blame’ and dynamic censure to justify the relevance of considering the qualitative conditions of imprisonment at sentencing as well as during the administration of the sentence. This framework is coupled by a typology of unjustified harmful carceral conditions that can be considered relevant evidence. This expanded purview of sentencing will offer greater legitimacy of punishment by strengthening communicative practices of punishment that include dynamic censure, including censuring the state for additional and unjustified state‐created harms.
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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 | 0.010 | 0.051 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.004 | 0.018 |
| Scholarly communication | 0.005 | 0.009 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.002 | 0.003 |
| 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".