Development and Initial Validation of a Measure to Assess Factors Related to Sustainability of School-Wide Positive Behavior Support
Bibliographic record
Abstract
Sustainability of effective practices in schools is a critical area for research in any domain. The purpose of this article is to describe and evaluate the validity and reliability of a recently developed research instrument designed to evaluate schools’ capacity to sustain school-wide positive behavior support (SWPBS) efforts at the universal tier. The School-Wide Universal Behavior Sustainability Index–School Teams (SUBSIST) was created to assess factors (of the context, implementer practices, and outcomes) that enhance or prevent sustainability of SWPBS. Content of the web-based survey was identified through literature review, and initial validation analyses included ratings of content validity by an expert panel ( n = 21) and assessment of internal consistency, test–retest reliability, interrater reliability, and concurrent validity (with SWPBS fidelity of implementation data) through a pilot study ( n = 25). Results indicated strong psychometric properties for assessing sustainability. The authors discuss the results in terms of future research in enhancing SWPBS sustainability.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.030 | 0.039 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".