Carving out a place: Establishing a new nurse practitioner practice in rural and remote Canada.
Bibliographic record
Abstract
Across the country, the development of legislation and new employment opportunities are encouraging the implementation of nurse practitioners (NPs) in a variety of acute care and primary care settings. In the literature the roles and practices of NPs are reviewed primarily from the perspective of availability, quality, and accessibility of health care services. The NP is a new health care provider role, practicing independently in rural and remote communities. There is little information on how new NPs enter a community and establish a practice or what sustains them in their practice. There is limited research, particularly in the Canadian health care context from the perspective or NPs themselves. Without the perspective of the experiences of establishing a new NP practice in rural and remote communities, knowledge of appropriate, context specific supports to recruit and retain NPs in rural communities is limited. This thesis is a qualitative interpretive study of the experiences of nurse practitioners as they establish new NP practices in rural and remote communities across Canada. The data for this study is from in-depth interviews conducted with six nurse practitioners for the Nature of Nursing Practice in Rural and Remote Canada Study. Carving out a place for practice was found to be a challenging process that requires time and support in order for the NP to develop a presence in the community. As the first and only NPs in their communities, resources including appropriate policies, administrative and clerical support, and mentorship opportunities are needed to support the development of these new roles and promote job satisfaction and ultimately retention of these much needed health care providers.'
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.030 | 0.009 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.001 | 0.003 |
| 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".