Bibliographic record
Abstract
This set of articles on psychotherapy training looks forward along 3 lines. The intent is to illuminate a selection of key issues facing psychotherapy educators in Canada at the present juncture, examining each with sufficient depth to provide a rational basis for recommendations on future directions. The review has been composed to address psychotherapeutic educational content, the form in which such education is delivered, and the overarching theoretical framework within which specific training takes place. Taken together, these papers consider psychotherapy education increasingly informed by process and outcome research literature, reflecting an integrative perspective, and delivered in innovative ways that are attentive to current knowledge about best educational practices. The authors have considered education at both postgraduate and continuing educational levels of training. A recent review of postgraduate psychiatric training in Canada emphasized several themes (1–3). Some thematic overlap is apparent with the articles comprising the current review: they underscore the importance of evidence-based training and critical appraisal of the evolving scientific literature, evaluation of trainee competence, a broad skill set with a capacity for integrative case formulation, and facilitation of continued learning throughout psychiatrists’ careers.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.012 | 0.040 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.006 | 0.005 |
| Science and technology studies | 0.003 | 0.005 |
| Scholarly communication | 0.009 | 0.006 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.009 | 0.010 |
| Insufficient payload (model declined to judge) | 0.005 | 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".