PROFESSORS' VIEWS ON MENTAL HEALTH NURSING EDUCATION IN THE BACCALAUREATE NURSING PROGRAMS OF ONTARIO: A GROUNDED THEORY APPROACH
Bibliographic record
Abstract
According to the Canadian Nurses??? Association (2005), mental health (MH) nursing is currently undervalued in the nursing profession. The Education Committee of the Canadian Federation of Mental Health Nurses (CFMHN) (2009) reports that the length of MH theory and practicum varies enormously in the undergraduate nursing programs of Ontario and across the country. Interviews with 19 nursing professors representing programs with different MH components show a variation in their opinions about topics such as the degree of importance of a mandatory stand-alone MH component, whether MH nursing education should be students??? or professors??? responsibility, how professors relate themselves to the MH component, and their familiarity with and assessment of their program???s MH education. It remains unclear the extent to which these factors contribute to program design and, in turn, students??? knowledge of MH nursing. Further research in this area is required.
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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 | 0.012 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.016 | 0.011 |
| Scholarly communication | 0.007 | 0.002 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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".