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Record W2171004060 · doi:10.1177/1049731514521302

Fresh Start

2014· article· en· W2171004060 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueResearch on Social Work Practice · 2014
Typearticle
Languageen
FieldSocial Sciences
TopicCriminal Justice and Corrections Analysis
Canadian institutionsUniversity of Windsor
Fundersnot available
KeywordsRecidivismModerationPsychologyUnivariateClinical psychologyMeta-analysisMultivariate statisticsJuvenileSample size determinationMultivariate analysisDemographyMedicineStatisticsSocial psychologyInternal medicineBiology

Abstract

fetched live from OpenAlex

Objectives: A meta-analysis was conducted in order to generate more understanding regarding the efficacy of aftercare programs in reducing the recidivism rates of juvenile offenders reentering their communities following a period of custody. Method: 30 eligible primary studies were obtained through a systematic literature review and were coded. Recidivism was the outcome variable and 11 moderating variables were grouped according to either a sample, treatment, methodological, or study characteristic. A summary effect size was computed while moderator analyses and meta-regression were also conducted. Results: The summary effect size of aftercare programs was non-significant but subgroup univariate and multivariate analyses yielded significant treatment effects for samples of youth who averaged over 16.5 years of age and whose predominant index offense was violent. Well-implemented aftercare programs also yielded substantial treatment effects. Conclusion: The findings suggest that under specific conditions aftercare can reduce recidivism rates for youth involved in the juvenile justice system.

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.

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)0.009
metaresearch head score (Gemma)0.011
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Science and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.916
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0090.011
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.003
Science and technology studies0.0050.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.002

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 head0.200
GPT teacher head0.512
Teacher spread0.312 · 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