To Boldly Go: A Partnership Enterprise to Produce Applied Health and Nursing Services Researchers in Canada
Bibliographic record
Abstract
This paper describes the origins of the Regional Training Centres (RTCs) from the perspective of the Canadian Health Services Research Foundation (CHSRF), a national funder of applied health and nursing services research in Canada. The author details the contributions of CHSRF, Canadian Institutes of Health Research (CIHR) and Capacity for Applied and Developmental Research and Evaluation (CADRE) program, as well as an essential feature of the RTCs: their application of the linkage and exchange model (Lomas 2000). The discussion encompasses the RTC program requirements and selection process, as well as the fourth-year review, the aim of which was to assess the early results of the RTCs. The role that CHSRF plays in facilitating the national network of RTCs is highlighted. The author concludes with reflections on what has worked well, what might be done differently and advice to others interested in developing graduate education based on the linkage and exchange model.
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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 | 0.026 | 0.023 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.013 | 0.003 |
| Scholarly communication | 0.008 | 0.002 |
| Open science | 0.003 | 0.008 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.008 | 0.002 |
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".