Implementing Evidence-Based Practices in School Psychology: Excavation by De-Implementing the Disproved
Bibliographic record
Abstract
The scientist-practitioner model of practice is the most common approach to the profession of school psychology and embraces evidence-based practices as foundations of clinical practice. The focus on evidence-based practices involves not only using the preponderance of research to determine what works, but also how to implement these practices effectively. An important impediment to implementing innovative evidence-based practices is that interventions and practices that have been proved ineffective or of low value continue to be used in education and psychology. What are the issues that assist in discontinuing practices that are widely used, but have been disproved or are otherwise problematic? How can room be made for more effective, innovative, and evidence-based practices? This issue of the Canadian Journal of School Psychology is devoted to exploration of different forms of disproved, low value, or problematic practices, factors that keep these practices alive in schools, and how to best de-implement ineffective and problematic practices. If the scientist-practitioner model is to be defined largely by the implementation of evidence-based practices, then de-implementation will be a critical aspect in the evolution of the profession of school psychology.
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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 | 0.163 | 0.227 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.009 | 0.006 |
| Science and technology studies | 0.014 | 0.134 |
| Scholarly communication | 0.028 | 0.030 |
| Open science | 0.006 | 0.020 |
| Research integrity | 0.010 | 0.026 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".