Contemplating Place in Nursing: Ontological Understandings
Bibliographic record
Abstract
How a nurse understands and integrates their understanding of place is important to nursing practice. In this paper we explore the concept of place in relation to our varied backgrounds and with the understanding and idea that the concept of place differs from one person to another depending upon their experiences. By purposefully coming together to talk about place and its intersection between our common circumstances, interests and beliefs we share and discuss the realm of place as home, relationship(s), and holding memories. Each of our unique and distinct identities, such as being Mi’kmaw, Métis, Jewish, and a Newcomer to Canada, brought varied perspectives of how place is integrated into our lives and our work as nurses. When we pay close attention, we can begin to understand that nursing research, practice and education is entwined with place and through this with spirit, and healing, having implications for health and wellbeing.
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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 | 0.013 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.011 | 0.102 |
| Scholarly communication | 0.013 | 0.022 |
| Open science | 0.003 | 0.013 |
| Research integrity | 0.005 | 0.007 |
| 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".