Punishing while Presuming Innocence : A Study on Bail Conditions and Administration of Justice Offences
Bibliographic record
Abstract
This paper examines the process and outcomes of bail hearings, focusing on cases where defendants’ hearings involved administration of justice and sentencing offences. The data analyzed for this project suggests that despite the presumption of innocence and non-punitive official objectives of judicial release, the practice by law enforcement and courts at this stage of the process tends towards punitiveness. These punitive responses are illustrated by three main findings that relate to the detention of individuals accused of administration of justice or sentencing offences, the number of conditions of release breached per combination of charges, and the breached conditions of release. These processes are understood through a durkheimian lens, using Fauconnet’s work which considers the social function of punitive processes as focused on annihilating the criminal act to establish social order. As will be seen, this function is achieved through the selection of a scapegoat that is rapidly punished, rather than appropriately assigning individual liability.
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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 | 0.005 | 0.028 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.005 | 0.005 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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".