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Record W4319845277 · doi:10.1002/cl2.1304

PROTOCOL: The effects of resettlement/re‐entry services on crime and violence in children and youth: A systematic review

2023· review· en· W4319845277 on OpenAlexaff
Jennifer S. Wong, Chelsey Lee, Natalie Beck

Bibliographic record

VenueCampbell Systematic Reviews · 2023
Typereview
Languageen
FieldHealth Professions
TopicHomelessness and Social Issues
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsPsychological interventionIntervention (counseling)PsychologyEthnic groupProtocol (science)Clinical psychologyMedicinePsychiatryPolitical scienceAlternative medicine

Abstract

fetched live from OpenAlex

This is the protocol for a Campbell systematic review. The goal of the study is to examine the impacts of aftercare/resettlement interventions on youth with respect to criminogenic outcomes, and to examine factors related to intervention success. Specific objectives are as follows: (1) What is the impact of aftercare/resettlement interventions on youth with respect to outcomes of crime and violence? (2) How is the treatment effect of aftercare/resettlement interventions on crime and violence outcomes moderated by factors such as participant (e.g., age, race, ethnicity, sex, offender type), treatment (e.g., intensity and quality of implementation), methodological (e.g., measurement of crime, study design, timing of follow-up measures), and study characteristics (e.g., date of publication, peer-reviewed status)? (3) Are some types of aftercare/resettlement interventions more effective than others? (4) What are the barriers and facilitators to effective implementation of aftercare/resettlement interventions? (5) What are the mechanisms (theory of change) underlying aftercare/resettlement interventions? (6) What does the available research suggest regarding the cost of aftercare/resettlement interventions?

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)0.098
metaresearch head score (Gemma)0.153
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Protocol · Consensus signal: Protocol
Teacher disagreement score0.124
Threshold uncertainty score0.520

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0980.153
Meta-epidemiology (narrow)0.0060.007
Meta-epidemiology (broad)0.0190.015
Bibliometrics0.0150.015
Science and technology studies0.0050.006
Scholarly communication0.0120.011
Open science0.0060.007
Research integrity0.0090.010
Insufficient payload (model declined to judge)0.1240.016

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 head0.121
GPT teacher head0.472
Teacher spread0.351 · 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 designSystematic review
Domainnot available
GenreProtocol

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

Citations3
Published2023
Admission routes1
Has abstractyes

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Same venueCampbell Systematic ReviewsSame topicHomelessness and Social IssuesFrench-language works237,207