“Lively Combat”: Kathleen Ellis and the Canadian Nurses Association’s Lobby during the Second World War
Bibliographic record
Abstract
Although it has become unfashionable in recent years to extol the achievements of those who have become known as the "elite" in Canadian nursing, it is nonetheless true that a number of early Canadian nurse leaders contributed significantly to the advancement of their profession. One such individual was Kathleen Wilhelmina Ellis. This article analyzes her impact as Emergency Nursing Advisor for the Canadian Courses Association (CNA) during World War II. The previously unreported success of the CNA in capitalizing on the "crisis" of world War II to counter plans of the Canadian Hospital Council to increase pupil nurse enrollments beyond hospitals' clinical teaching and supervision capabilities provides the context for analysis. From 1942 to 1946, the CNA administered a $774,000 grant from the Federal Government to improve teaching in hospital and university schools of nursing, provide bursaries for graduate nurses, and recruit increased numbers of qualified applicants to hospital nurse training programs. The success of the CNA in securing and administering these funds signalled its political acumen as national representative of Canadian nurses and nursing. Kathleen Ellis' contribution as Emergency Nursing Advisor for the CNA was important to the success of the CNA's lobby during World War II.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.046 | 0.016 |
| Scholarly communication | 0.009 | 0.003 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.005 | 0.007 |
| 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".