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Record W2804591908 · doi:10.3102/0013189x18776975

Factors Predicting Sustained Implementation of a Universal Behavior Support Framework

2018· article· en· W2804591908 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueEducational Researcher · 2018
Typearticle
Languageen
FieldPsychology
TopicBehavioral and Psychological Studies
Canadian institutionsUniversity of British Columbia
FundersInstitute of Education Sciences
KeywordsFidelityPsychological interventionPsychologyStructural equation modelingApplied psychologyComputer scienceStatisticsMathematics

Abstract

fetched live from OpenAlex

In this 3-year prospective study, we tested the extent to which school-, practice-, and district-level variables predicted sustained implementation for schools in various stages of implementation of school-wide positive behavioral interventions and supports (SWPBIS) Tier 1 (universal) systems. Staff from 860 schools in 14 U.S. states completed a research-validated measure of factors associated with sustained implementation of school interventions during Year 1 of this study. Analyses included multigroup structural equation modeling of school and district implementation fidelity data. Results indicated that adequate implementation fidelity and better Team Use of Data for decision making in Study Year 1 were the strongest predictors of sustained implementation in Year 3. In addition, the number of other schools in the district adopting SWPBIS was a similarly strong predictor. A critical mass of schools implementing was also predictive, especially for schools earlier in implementation. School characteristics were not predictive, except for grade levels served, which was an inconsistent predictor by stage.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.092
Threshold uncertainty score0.909

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0920.000

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 head0.364
GPT teacher head0.523
Teacher spread0.160 · 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