Effective behavior support (EBS): "where we have been, where we are going"
Bibliographic record
Abstract
Effective behavior support (EBS) is a school-wide program that helps the school put strategies in place to teach children positive behavior. Students and staff embark on a journey together to make their school a rich environment for student learning. Research has shown that if students behave positively in their school, their academic performance can change. Over the past five years, our school has embarked on the journey to engage students in positive behavior. This action research project explored my school's current practices and allowed me to engage in critical dialogue with my colleagues to gain new insight and explore new paths to improve my practice for implementing the practices of EBS. As a coach of EBS, I felt it was time to look deeper into what we have done, what we are doing, and where we could go from here. There is a need to amalgamate our information, scrutinize our data, and put together an action plan proposal in order to ensure that our school stays on the positive behavior track on which it has been. --P. i.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.013 | 0.005 |
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".