Furthering Anti-Racist Practice: Reconciliation in Action (RéconciliACTION) (Discussion Paper)
Bibliographic record
Abstract
Nursing scholarship and practice has been historically complicit in the (re)production of racial inequities by not acknowledging and countering their part in the legacy of colonization . This paper will discuss the implementation of an experiential transformative learning project, RéconciliACTION, grounded in critical social justice theory. Four elements – testimonial authority, experiential learning, reciprocity, and relationality - can be implemented in nursing education that value lived experience to create change toward address anti-Indigenous racism in educational settings and health institutions. Lessons from the RéconciliACTION Project reinforce the need to increase nursing educators' knowledge of such methods and practices. Essential to this process is the recognition of lived experience as knowledge via Testimonial Authority. The process of transformation begins with the integration of anti-racist practices and Indigenous content. This project seeks to create leaders and allies in the journey towards reconciliation, reducing anti-racist attitudes and practices in educational and medical facilities
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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 | 0.023 | 0.022 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.011 | 0.019 |
| Scholarly communication | 0.008 | 0.007 |
| Open science | 0.002 | 0.014 |
| Research integrity | 0.005 | 0.008 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".