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Record W2114582981 · doi:10.1177/1534508414556503

Variables Associated With Enhanced Sustainability of School-Wide Positive Behavioral Interventions and Supports

2014· article· en· W2114582981 on OpenAlexaff
Kent McIntosh, Jerin Kim, Sterett H. Mercer, M. Kathleen Strickland-Cohen, Robert H. Horner

Bibliographic record

VenueAssessment for Effective Intervention · 2014
Typearticle
Languageen
FieldPsychology
TopicBehavioral and Psychological Studies
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsSustainabilityPsychological interventionPsychologySample (material)Applied psychologyMedical educationMedicineEcology

Abstract

fetched live from OpenAlex

Practice sustainability is important to ensure that students have continued access to evidence-based practices. In this study, respondents from a national sample of 860 schools at varying stages of implementing School-Wide Positive Behavioral Interventions and Supports (SWPBIS) were administered a research-validated measure of factors predicting sustained implementation of school-based practices. School demographic characteristics and specific school team actions were assessed to indicate which variables were most strongly associated with four empirically-derived sustainability factors. Findings showed that, in general, school demographic characteristics were not significantly related to sustainability. School team actions, especially the frequency of sharing data with the whole school staff, were statistically significantly related to sustainability. Implications for enhancing sustainability of school-based practices are discussed.

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)0.004
metaresearch head score (Gemma)0.023
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 score0.004
Threshold uncertainty score0.020

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.023
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.001
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 head0.048
GPT teacher head0.413
Teacher spread0.366 · 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

Citations57
Published2014
Admission routes1
Has abstractyes

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