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Circles of Support for Sex Offenders

2017· other· en· W4248839113 on OpenAlexaff
Alan Dudley Brown

Bibliographic record

VenueThe Encyclopedia of Corrections · 2017
Typeother
Languageen
FieldPsychology
TopicPsychopathy, Forensic Psychiatry, Sexual Offending
Canadian institutionsMount Saint Vincent University
Fundersnot available
KeywordsRecidivismSecrecyPrisonCriminologyPsychologyAccountabilityIsolation (microbiology)Computer securitySocial psychologyPolitical sciencePublic relationsComputer scienceLaw

Abstract

fetched live from OpenAlex

Abstract Circles of Support and Accountability (CoSA) is a community‐based restorative approach that focuses on the difficulties associated with sex offenders deemed at high risk for reoffending upon release from prison. At the end of their custodial sentences, many charged with sexual offences find themselves isolated and faced with limited resources to draw upon as they attempt to reintegrate into their communities. The goal of CoSA is to assist individuals who have been charged with sexual offenses in their efforts to lead responsible and productive lives. The mission of the organization is captured by its dual guiding principles: “No more victims” and “No one is disposable.” Through regular contact at circle meetings and other forms of pro‐social interaction, offenders released into the community are able to develop a series of tools to assist them in combating the secrecy and isolation that has been routinely shown to increase recidivism and to decrease community safety.

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)0.001
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: Other · Consensus signal: Other
Teacher disagreement score0.061
Threshold uncertainty score0.205

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.012
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0060.002
Scholarly communication0.0060.003
Open science0.0010.009
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0610.005

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 head0.030
GPT teacher head0.334
Teacher spread0.304 · 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
GenreOther

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

Citations0
Published2017
Admission routes1
Has abstractyes

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