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Record W1992566977 · doi:10.1177/0829573514540266

Effects of Implementing School-Wide Positive Behavioural Interventions and Supports on Problem Behaviour and Academic Achievement in a Canadian Elementary School

2014· article· en· W1992566977 on OpenAlexaffabout
Joanna L. Kelm, Kent McIntosh, Sharon Cooley

Bibliographic record

VenueCanadian Journal of School Psychology · 2014
Typearticle
Languageen
FieldPsychology
TopicBehavioral and Psychological Studies
Canadian institutionsThompson Rivers UniversityUniversity of British Columbia
Fundersnot available
KeywordsPsychological interventionPsychologyFidelityAcademic achievementPerceptionDevelopmental psychologyMedical educationApplied psychologyMedicine

Abstract

fetched live from OpenAlex

Although there is much research on School-Wide Positive Behavioural Interventions and Supports (PBIS) in the United States, there is little such research in Canada. The purpose of the current study was to provide a case study example of the relation between implementing PBIS and student academic and behavioural outcomes, as well as student perceptions of the school environment. Data were collected in one school as it moved from partial to full implementation of PBIS. The results of the study indicated positive academic and behavioural outcomes for students, as well as increased perceptions of safety, understanding of school expectations, and decreased perceptions of bullying. The results of this study are discussed with implications regarding PBIS in Canada and the importance of fidelity of implementation of school-based 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)0.002
metaresearch head score (Gemma)0.005
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 score0.074
Threshold uncertainty score0.534

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.002
Science and technology studies0.0110.001
Scholarly communication0.0020.000
Open science0.0020.002
Research integrity0.0010.002
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 head0.079
GPT teacher head0.365
Teacher spread0.286 · 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

Citations35
Published2014
Admission routes2
Has abstractyes

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