Factors Predicting Sustained Implementation of a Universal Behavior Support Framework
Why this work is in the frame
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Bibliographic record
Abstract
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.
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.092 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it