De la clinique à la recherche : l’auto-ethnographie comme outil d’analyse des transitions identitaires du chercheur en sciences infirmières
Bibliographic record
Abstract
The scientific legitimacy of nursing research depends on its adherence to different scientific criteria. Despite the lack of consensus on predetermined criteria, reflexivity is widely discussed as a strategy to establish rigour in qualitative research. Unfortunately, with the exception of tools such as the reflexive journal, little is said about how reflexivity can be completed. Several recent studies suggest the relevance of autoethnography to support the reflexive approach of nurse researchers. Inspired by the findings of an autoethnography and a narrative literature review, this article examines how this approach can contribute to the reflexivity of the nurse researcher. Autoethnography seems particularly adapted to the professional and academic context in which many nurses evolve. As a reflective tool, autoethnography can promote the development of the researcher's self-awareness, provide analytical tools to help better understand the influence of previous experiences on the relationship to research and report on the transition between different professional identities. In order to contribute to the debate on the use of autoethnography in qualitative research, central elements to this approach are discussed.
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 | 0.274 | 0.080 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.006 |
| Science and technology studies | 0.002 | 0.018 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.006 | 0.011 |
| Insufficient payload (model declined to judge) | 0.001 | 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; both teacher heads agree on what is shown here.
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".