MétaCan
Menu
Back to cohort
Record W2023719257 · doi:10.7870/cjcmh-2001-0020

An Evaluation of Residential Treatment Programs for Young Offenders in the Waterloo Region

2001· article· en· W2023719257 on OpenAlexafffundvenue
Bruce A. Bidgood, S. Mark Pancer

Bibliographic record

VenueCanadian Journal of Community Mental Health · 2001
Typearticle
Languageen
FieldHealth Professions
TopicHomelessness and Social Issues
Canadian institutionsWilfrid Laurier UniversityUniversity of Windsor
FundersWilfrid Laurier University
KeywordsPsychologyClinical psychology

Abstract

fetched live from OpenAlex

This paper chronicles a comprehensive evaluation of 6 residential facilities for young offenders located within the region of Waterloo. Two kinds of research methodologies were employed in the investigation. One was primarily quantitative in nature, involving the completion of standardized scales for each of the youths who participated in the study (N = 129). The other was qualitative in nature, and involved interviews with a small sample of "graduates" from the centres (N = 9), and some of their parents and guardians (N = 4). Residential treatment was associated with significant improvements on the 2 measures developed specifically for the evaluation: a measure which focused on the specific goals which had been assigned to youths while in the program (Catalogue of Goals for Youth in Residence), and the global index of youth functioning which was empirically generated from residential case files (Inventory of Work Life and Social Skills). Qualitative interviews with program graduates and selected parents and guardians generally confirmed the positive evaluation of the impact of residential facilities on youths and served as the foundation for a series of recommendations for programmatic modifications and improvements.

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)0.002
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.925
Threshold uncertainty score0.149

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0030.001
Scholarly communication0.0010.001
Open science0.0020.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.283
GPT teacher head0.489
Teacher spread0.206 · 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 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
Published2001
Admission routes3
Has abstractyes

Explore more

Same venueCanadian Journal of Community Mental HealthSame topicHomelessness and Social IssuesFrench-language works237,207