Predicting Abandonment of School-wide Positive Behavioral Interventions and Supports
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.
Bibliographic record
Abstract
This study examines predictors of abandonment of evidence-based practices through descriptive analyses of extant state-level training data, fidelity of implementation data, and nationally reported school demographic data across 915 schools in three states implementing school-wide positive behavioral interventions and supports (SWPBIS). Schools included in this study were tracked for a 5-year period after initial training, yet some elected to abandon SWPBIS at various times during implementation. Results showed that a small proportion of schools in the sample abandoned SWPBIS (7%). Logistic regression analysis identified school locale as the only statistically significant predictor of SWPBIS abandonment with schools located in cities being more likely to abandon. Results are discussed in terms of addressing types of schools at greater risk for abandonment and the importance of state-level training and coaching support.
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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) | 0.003 | 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