Bibliographic record
Abstract
Abstract This chapter examines the question: “How should polities respond to repeat offenders whose demonstrated willingness to use violence makes then dangerous to the public?” It critiques three themes commonly seen in discussions of dangerous offenders and how societies may respond to them, especially using criminal law: (1) that “dangerousness” should be understood as a prediction of future violence, (2) that polities have a positive “duty to protect” their members from criminal violence, a duty they may fulfill by imprisoning dangerous offenders so long as they continue to be dangerous, and (3) that the right to self-defense can justify the indefinite detention of dangerous offenders It is argued that the incarceration of individuals on purely preventive grounds—to prevent future violence—cannot be reconciled with our concept of punishment. Nor can it comply with multiple constraints states must adhere to if their systems of criminal punishment are to be morally acceptable (e.g., proportionality between the harshness of punishments and the seriousness of crimes for which they are imposed, parity, double jeopardy, and fair notice). Finally, the chapter suggests an alternative to extant legal practices and philosophical theories of punishment that may reconcile the incarceration of dangerous offenders with justice: it requires that we (1) reconceptualize dangerousness as a current dispositional property rather than a prediction of future behavior and (2) show that this property can be within the control of an offender. When dangerousness is seen as a controlled disposition we may criminalize “being a persistent violent dangerous offender” as a status crime. Some of the contours of this new crime are then described.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.174 | 0.039 |
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".