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Record W2139834616 · doi:10.1080/01609510903366186

Releasing the Steam: An Evaluation of the Supporting Tempers, Emotions, and Anger Management (STEAM) Program for Elementary and Adolescent-Age Children

2010· article· en· W2139834616 on OpenAlexafffund
Bruce A. Bidgood, Heather Wilkie, Annette Katchaluba

Bibliographic record

VenueSocial Work With Groups · 2010
Typearticle
Languageen
FieldSocial Sciences
TopicEarly Childhood Education and Development
Canadian institutionsRegional Municipality of WaterlooUniversity of WindsorUniversity of Northern British Columbia
FundersWilfrid Laurier University
KeywordsAnger managementAngerIntervention (counseling)PsychologyDevelopmental psychologyClinical psychologyPsychiatry

Abstract

fetched live from OpenAlex

This paper chronicles an evaluation of the Supporting Tempers, Emotions, and Anger Management (STEAM), a school-based emotion management program for elementary and adolescent age children. A quasi-experimental design was used to assess the program impacts as reported by children, their parents, and teachers. The results revealed that STEAM was associated with an array of significant positive changes in both the home and school environment. The program was particularly effective with young children (Grades 1–3) relative to students in the older age cohorts (i.e., Grades 4–6 and 7–8). The findings suggest the importance of early intervention to assist children in the development of emotion management.

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)0.003
metaresearch head score (Gemma)0.002
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 score0.003
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.001
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 head0.020
GPT teacher head0.323
Teacher spread0.303 · 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

Citations12
Published2010
Admission routes2
Has abstractyes

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