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Support and Accountability

2016· other· en· W4246891334 on OpenAlexaff
Robin Wilson, Kathryn J. Fox, Andrew J. McWhinnie

Bibliographic record

Venuenot available
Typeother
Languageen
FieldSocial Sciences
TopicCriminal Justice and Corrections Analysis
Canadian institutionsMcMaster University
Fundersnot available
KeywordsAccountabilityProsocial behaviorMotivational interviewingPsychological interventionGovernment (linguistics)PsychologyEconomic JusticePerspective (graphical)Restorative justicePublic relationsPolitical scienceCriminologySocial psychologyPsychiatry

Abstract

fetched live from OpenAlex

Abstract In spite of credible evidence to the contrary, a perspective remains that sexual violence remains a problem out of control. The past 30 years have seen advances in the assessment, treatment, and risk management of sex offenders, and government‐reported rates of reoffending are at all‐time lows. Central to these gains is the idea that interventions must not only restrict access to potential victims and high‐risk situations, but also promote the development of balanced, self‐determined lifestyles. A focus on strength‐based approaches, the rise of motivational interviewing, and greater collaboration amongst stakeholders has dramatically changed the risk management endeavour. An initiative that seeks to meld these important aspects is Circles of Support and Accountability, a restorative justice‐informed model of wraparound care for high‐risk/need sex offenders. Trained community volunteers collaborate with professionals to provide prosocial support to offenders while holding them accountable for their behaviour on re‐entry, with results showing significant reductions in post‐release reoffending in all domains.

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)0.023
metaresearch head score (Gemma)0.123
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 score0.059
Threshold uncertainty score0.198

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0230.123
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.001
Science and technology studies0.0070.010
Scholarly communication0.0160.009
Open science0.0020.014
Research integrity0.0050.007
Insufficient payload (model declined to judge)0.0590.007

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 head0.021
GPT teacher head0.350
Teacher spread0.329 · 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
Published2016
Admission routes1
Has abstractyes

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