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Record W3135674092

The Chemical Castration of Recidivist Sex Offenders inCanada: A Matter of Faith

2010· article· en· W3135674092 on OpenAlexvenueno aff
Matthew R Kutcher

Bibliographic record

VenueDalhousie law journal · 2010
Typearticle
Languageen
FieldEnvironmental Science
TopicWildlife Conservation and Criminology Analyses
Canadian institutionsnot available
Fundersnot available
KeywordsFaithCriminologyCastrationLawPolitical sciencePsychologyPhilosophyTheologyMedicineInternal medicine
DOInot available

Abstract

fetched live from OpenAlex

Chemical castration refers to the use of medication to reduce male testosterone to pre-pubertal levels. Since the mid-20th century reports have detailed this practice in attempts to control pathological sexual behaviour. In 2006, the Canadian Federal Court of Appeal ruled it constitutional for the National Parole Board to require that recidivist sex offenders, if found to be long-term offenders, be chemically castrated under their conditions of release. This paper examines the chemical castration of recidivist sex offenders in Canada through a review of long-term offender hearings reported between 1997 and 2009. The practice is analyzed from ethical, medical and legal perspectives. It is concluded that chemical castration of sex offenders is ethically problematic, that evidence for its effectiveness in preventing recidivism is limited and of poor quality and that judges should avoid excessive reliance on chemical castration when deciding to grant conditional release to recidivist sex offenders.

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)0.002
metaresearch head score (Gemma)0.012
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: Empirical
Teacher disagreement score0.841
Threshold uncertainty score0.316

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.012
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0040.002
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0010.003
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 head0.014
GPT teacher head0.230
Teacher spread0.216 · 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

Citations4
Published2010
Admission routes1
Has abstractno

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