Help Us Chart a Course for Canada's Nursing Professions
Bibliographic record
Abstract
Building the Future Over the past two years, many nurse leaders have participated in Building the Future, the first national study led and endorsed by Canada’s nursing stakeholder groups. The study’s overriding goal is to develop an integrated, longterm labour market strategy for Licensed Practical Nurses (LPNs), Registered Nurses (RNs) and Registered Psychiatric Nurses (RPNs). Through interviews, surveys, focus groups and other strategies, the first phase of the study is focused on gathering current, comprehensive information on all aspects of the nursing labour market. These efforts are helping us paint a current picture of nursing human resources, project long-term requirements, develop options to improve retention and recruitment, and assist in developing an integrated strategy for nursing human resources in Canada. We will soon be moving into the second phase of the study, which will involve consultations with provincial governments as well as nursing stakeholder groups to achieve consensus on key issues and possible solutions. The input of nursing leaders will be extremely valuable in this phase. Building the Future urges you to participate and to collaborate with our stakeHelp Us Chart a Course for Canada’s Nursing Professions
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.018 | 0.003 |
| Scholarly communication | 0.007 | 0.002 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.006 | 0.007 |
| Insufficient payload (model declined to judge) | 0.096 | 0.021 |
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".