Northern nursing practice in a primary health care setting
Bibliographic record
Abstract
BACKGROUND: This paper explicates the nature of outpost nursing work, and/or the day-to-day realities of northern nursing practice in a primary health care setting in Canada. The study was carried out to systematically explore the work of nurses in an indigenous setting. Institutional ethnography, pioneered by Dorothy Smith was the methodology used to guide this research. The theoretical perspective of this methodology does not seek causes or links but intends to explicate visible practices. AIM: It is intended to explicate the social organization of specific discourses that inform work processes of nurses working in remote indigenous communities. METHODOLOGY: The data originated from various sources including spending 2 weeks in a northern remote community shadowing experienced nurses, taking field notes and audio taping interviews with these nurses. One of the two researchers was a northern practice nurse for many years and has had taught in an outpost nursing programme. As part of the process, texts were obtained from the site as data to be incorporated in the analysis. The lived experiences have added to the analytical understanding of the work of nurses in remote areas. Data uncovered documentary practices inherent to the work setting which were then analysed along with the transcribed interviews and field notes derived from the on-site visit. Identifying disjuncture in the discourse of northern nursing and the lived experience of the nurses in this study was central to the research process. RESULTS: The results indicated that the social organization of northern community nursing work required a broad generalist knowledge base for decision making to work effectively within this primary health care setting. The nurse as 'other' and the invisibility of nurses' work of building a trusting relationship with the community is not reflected in the discourse of northern nursing. Trust cannot be quantified or measured yet it is fundamental to working effectively with the community. CONCLUSION: The nurses in this study saw building trust to promote health and well-being in communities as very important, yet very difficult to achieve. The difficulty in part stems from the constraining, structural, administrative, historical, cultural and political contextual realities that have shaped northern community nursing.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.003 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".