MétaCan
Menu
Back to cohort
Record W2508961171 · doi:10.35502/jcswb.4

Case planning and recidivism of high risk and violent adult probationers

2016· article· en· W2508961171 on OpenAlexaffvenueabout
Delphine Gossner, Terri Simon, Brian Rector, Rick Ruddell

Bibliographic record

VenueJournal of Community Safety and Well-Being · 2016
Typearticle
Languageen
FieldPsychology
TopicPsychopathy, Forensic Psychiatry, Sexual Offending
Canadian institutionsUniversity of Regina
Fundersnot available
KeywordsRecidivismCompleteness (order theory)PsychologySample (material)Risk assessmentRisk managementActuarial scienceCriminologyBusinessComputer securityComputer scienceFinance

Abstract

fetched live from OpenAlex

This research examined the relationship between case planning indicators and recidivism for a sample of medium and high risk Canadian probationers sampled from two separate probation offices operating under the same policies and standards. A scale that measured completeness of case planning based on an evidence-based, outcome-focused case planning model called Community Safety Planning, revealed significant differences in case planning completeness between the samples with the probation office reporting higher levels of completeness demonstrating significantly lower levels of recidivism. This effect was also observed when investigating the entire sample; high-risk probationers with more complete case plans had 52 per cent less recidivism than high-risk probationers with less complete case plans. The nature of communication between probation and police services on an individual case basis was also examined in an effort to better understand how these partnerships are currently functioning, and whether there is opportunity to improve the strategic nature of the communication to achieve the common goal of community safety. Implications for best practices in case management with offender populations are offered.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.497
Threshold uncertainty score0.567

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.017
GPT teacher head0.284
Teacher spread0.268 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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
Published2016
Admission routes3
Has abstractyes

Explore more

Same venueJournal of Community Safety and Well-BeingSame topicPsychopathy, Forensic Psychiatry, Sexual OffendingFrench-language works237,207