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Record W2086400317 · doi:10.1177/0272431605285717

Effect of a Structured Arts Program on the Psychosocial Functioning of Youth From Low-Income Communities

2006· article· en· W2086400317 on OpenAlexaffabout
Robin Wright, Lindsay John, Stephen Ellenbogen, David R. Offord, Eric Duku, William Rowe

Bibliographic record

VenueThe Journal of Early Adolescence · 2006
Typearticle
Languageen
FieldSocial Sciences
TopicYouth Development and Social Support
Canadian institutionsMcMaster UniversityMcGill University
Fundersnot available
KeywordsPsychosocialThe artsPropensity score matchingPsychologyObservational studyMultilevel modelClinical psychologyMedicinePsychiatryPolitical scienceComputer science

Abstract

fetched live from OpenAlex

This study reports on the longitudinal examination of a structured arts program for Canadian youth, aged 9 to 15 years, from low-income communities. Evaluated were the extent to which community-based organizations successfully recruited and retained youth in the program and whether they demonstrated improvement with respect to artistic ability (combination of theatre, visual, and media arts) and psychosocial indicators. The results suggest successful recruitment and good retention rates. Multilevel growth curve analyses of observational and behavioral outcomes are presented. Observer ratings showed significant gains in artistic and social skills. Comparisons with matched controls using estimated linear propensity scores revealed a significant reduction in emotional problems for the intervention group. The overall conclusion is that youth from low-income communities benefit from structured arts programs.

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)0.001
metaresearch head score (Gemma)0.003
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.266
Threshold uncertainty score0.529

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.020
GPT teacher head0.286
Teacher spread0.266 · 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

Citations45
Published2006
Admission routes2
Has abstractyes

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