Bibliographic record
Abstract
Three nurse researchers came together in 2015 to conduct a study focusing on Indigenous learning within a Nurse Practitioner program in Canada. This work unfolds here as a series. The first, brings to the fore the researchers’ relationship with the research answering the question “Who am I in relation to the Research?” This is followed by an account of the research, “A call to action: Faculty perspectives of cultural safety within a nurse practitioner curriculum.” Coming to know the researchers’ experiences within the context of nursing education, practice and their personal life experiences became a vital activity, one that would drive and instigate the overall research endeavour. Through this integral process the researchers functioned also as participants where analysis was both self-interpretative and hermeneutic. Preunderstandings molded through societal, cultural and historical forces interconnected with meanings of Indigenous methodology. Unearthing root assumptions through critical dialogues and stories was found to illuminate embedded world-views that challenged pervasive colonial perceptions critical to understanding the interwoven nature of cultural safety and reconciliation. This writing may be of high interest for researchers and educators wishing to create and sustain culturally safe spaces in practice and learning environments.
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 | 0.013 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.036 | 0.054 |
| Scholarly communication | 0.023 | 0.010 |
| Open science | 0.002 | 0.013 |
| Research integrity | 0.004 | 0.012 |
| Insufficient payload (model declined to judge) | 0.003 | 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".