Community Health Nursing Vision for 2020
Bibliographic record
Abstract
As health care is shifting from hospital to community, community health nurses (CHNs) are directly affected. This descriptive qualitative study sought to understand priority issues currently facing CHNs, explore development of a national vision for community health nursing, and develop recommendations to shape the future of the profession moving toward the year 2020. Focus groups and key informant interviews were conducted across Canada. Five key themes were identified: community health nursing in crisis now, a flawed health care system, responding to the public, vision for the future, and CHNs as solution makers. Key recommendations include developing a common definition and vision of community health nursing, collaborating on an aggressive plan to shift to a primary health care system, developing a comprehensive social marketing strategy, refocusing basic baccalaureate education, enhancing the capacity of community health researchers and knowledge in community health nursing, and establishing a community health nursing center of excellence.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.015 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.012 | 0.006 |
| Scholarly communication | 0.012 | 0.007 |
| Open science | 0.002 | 0.016 |
| Research integrity | 0.008 | 0.009 |
| Insufficient payload (model declined to judge) | 0.007 | 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".