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Record W2164451018 · doi:10.7202/017325ar

Redresser les torts : l’abolitionnisme et le contrôle de la criminalité

2005· article· en· W2164451018 on OpenAlexvenueno aff
Willem de Haan

Bibliographic record

VenueCriminologie · 2005
Typearticle
Languageen
FieldSocial Sciences
TopicCriminal Justice and Corrections Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsAbolitionismPunishment (psychology)Perspective (graphical)Variety (cybernetics)RedressSociologyCriminologyHarm principleSocial controlPoliticsCriminal justiceState (computer science)Political scienceLaw and economicsLawSocial psychologyPsychologyHarm

Abstract

fetched live from OpenAlex

In this article 'abolitionism' will be discussed as a social movement, a theoretical perspective, and a political strategy. Strategies for penal reform will be dealt with and the implications of the abolitionist perspective for crime control will be discussed. As a theoretical perspective, abolitionism takes on the twofold task of providing a radical critique of the criminal justice system while showing that there are other, more rational ways of dealing with crime. It will be argued that what is needed is a wide variety o social responses rather than a uniform state reaction to the problem of crime. Therefore, a reconceptualization of the notions of crime and punishment is offered in the form of the concept of redress. In policy terms it is claimed that social policy instead of crime policy is needed in dealing with the social problems and conflicts that are currently singled as the problem of crime.

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 imitation

Not 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.

metaresearch head score (Codex)0.005
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.011
Threshold uncertainty score0.029

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.012
Scholarly communication0.0050.002
Open science0.0010.002
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0040.000

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.

Opus teacher head0.210
GPT teacher head0.429
Teacher spread0.219 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEmpirical

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".

Quick stats

Citations11
Published2005
Admission routes1
Has abstractyes

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