The CPA Presidential Task Force on Evidence-Based Practice of Psychological Treatments
Bibliographic record
Abstract
The Board of Directors of the Canadian Psychological Association (CPA) launched a Task Force on Evidence-Based Practice of Psychological Treatments to support and guide practice as well as to inform stakeholders. This article describes the work of this Task Force, outlining its raison d’etre, providing a comprehensive definition of evidence-based practice (EBP), and advancing a hierarchy of evidence that is respectful of diverse research methodologies, palatable to different groups, and yet comprehensive and compelling. The primary objective was to present an overarching methodology or approach to thinking about EBP so that psychologists can provide and implement the best possible psychological treatments. To this end, our intention for this document was to provide a set of guidelines and standards that will foster interest, encourage development, and promote effectiveness in EBP.
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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 | 0.304 | 0.341 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.005 | 0.004 |
| Bibliometrics | 0.022 | 0.015 |
| Science and technology studies | 0.013 | 0.014 |
| Scholarly communication | 0.014 | 0.007 |
| Open science | 0.009 | 0.011 |
| Research integrity | 0.016 | 0.028 |
| Insufficient payload (model declined to judge) | 0.011 | 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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".