Legacy and Evolution: Future Directions for the Canadian Nurses Association
Bibliographic record
Abstract
Established in 1908, the Canadian Nurses Association (CNA) has evolved through and survived many times of triumph and tumult over the decades (CNA 2024a). But few times have found CNA in a tougher position than it is in today as we juggle the need to provide strong and effective advocacy, stewardship of the profession, a wide range of member services and a constant effort to attract voluntary members. Sustaining CNA as the national and global voice of professional nursing in Canada needs decisive support from the nurses of Canada. In this commentary, the current and past chief executive officers reflect on CNA's legacy of success and call on nurse leaders to rally support for an exciting and effective national professional association.
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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 | 0.028 | 0.037 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.038 | 0.023 |
| Scholarly communication | 0.019 | 0.016 |
| Open science | 0.005 | 0.009 |
| Research integrity | 0.023 | 0.026 |
| Insufficient payload (model declined to judge) | 0.018 | 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".