Two-eyed seeing, arts-based reflection and collaboration: Reflexivity tools for nursing practitioners working across cultures
Bibliographic record
Abstract
This paper explores how the use of reflexivity, an approach to knowledge construction and understanding, provided a structural framework for a doctoral student of psychology as she conducted a literature review and worked as a registered nurse in clinical practice. Her reflexive practice allowed for the exploration of perspectives, biases, values and knowledge system and therefore it added rigour, credibility and trustworthiness to both her literature review and clinical work. Although Janet is not a psychotherapist, her reflexive practice shaped the relationships she developed and influenced the care she provided to people living with diabetic foot ulcers because her therapeutic and community involvement overlapped. Janet’s reflexive practice helped her move beyond the delivery of physical wound care towards more inclusive and expansive relationships with individuals, communities, doctors, psychologists, and family members. As these collaborative and inclusive relationships developed, questions about struggles and socio-cultural knowing influenced her understandings and pushed at what she imagined holistic and culturally relevant care might involve. Because her clinical work was geographically located within Aboriginal communities, her reflexive practice was also informed by the principles of Two-Eyed Seeing. Writing, journaling, listening, conversations and creating ‘art-as-event’ are the strategies which serve as a resource for this paper. In addition, it is important to note this reflexive writing is collaborative and multi-disciplined (nursing, psychology, and education). Our collaboration resulted in opportunities to understand, challenge and value other perspectives born and experienced on landscapes unfamiliar to us as individuals, professionals and women working in communities.
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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 | 0.148 | 0.146 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.009 | 0.004 |
| Science and technology studies | 0.009 | 0.047 |
| Scholarly communication | 0.026 | 0.025 |
| Open science | 0.005 | 0.028 |
| Research integrity | 0.005 | 0.008 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".