Top “5 in 5” CNA responds to the National Expert Commission
Bibliographic record
Abstract
In our last column (Villeneuve and Mildon 2013), we shared the topics of 11 project charters developed by the Canadian Nurses Association to respond to the nine-point Call to Action of the National Expert Commission (NEC 2012).The lead recommendation of the NEC was to move Canada's ranking on five key population health and health system performance indicators into the "top five" internationally in five years.That recommendation by the NEC was intended to respond to Canada's mediocre (and in some cases deteriorating) ranking on a number of influential, internationally comparable population health and health system performance indicators.Throughout the tenure of the NEC, its members were troubled by those outcomes when set against constantly rising healthcare spending.Its place as the first recommendation reflects the determination of the commissioners that nurses must join with others to lead efforts required to shift that paradox.
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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 | 0.031 | 0.089 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.017 | 0.005 |
| Scholarly communication | 0.016 | 0.005 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.020 | 0.028 |
| Insufficient payload (model declined to judge) | 0.020 | 0.007 |
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".