Bibliographic record
Abstract
The magnificent voices of Indigenous women who want to restore, preserve and extend the beauty of Indigenous culture must be relocated and honoured as the last best hope of escaping the tragic impacts of colonization. This paper started as an exploration of New Zealand Indigenous scholar Irihapeti Ramsden’s extraordinary efforts to imbed Cultural Safety as a foundation for nursing training and unity of purpose for all community helpers to alter the trajectory of colonization and its tragic impacts on Indigenous peoples. It morphed into a celebration of the powerful ‘reflective topical auto-biographies’ or meta-narratives of adaptability and resilience all Indigenous people need to share as we recover and heal from intergenerational traumas inflicted in the name of civilization and racial supremacy. Transformative change starts with self discovery as Irihapeti Ramsden taught her student nurses. Women and children are the most poignant victims of that foolish colonial project and their survival stories can lead all humanity back to respectful and loving sustainability. Indigenous women’s resilience stories need a special space in academic literature. Their enduring women-spirit has always guided this First Nations to be better first as an Indigenous man and more importantly as a human being. Irihapeti Ramsden’s journey to put Cultural Safety out there in mainstream academia began with a powerful reflective inner healing journey. Her life and work was a remarkable gift to all. The title of this paper derives from Section Three of her PhD thesis. It must be shared throughout all the worlds’ spaces in need of decolonization. Her ultimately political meta-narrative to alter ignorance and arrogance within education, government and society is one all Indigenous writers and scholars must study and articulate across often culturally unsafe places and spaces within Canada’s colleges and universities.
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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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.025 | 0.030 |
| Scholarly communication | 0.010 | 0.008 |
| Open science | 0.002 | 0.010 |
| Research integrity | 0.004 | 0.008 |
| Insufficient payload (model declined to judge) | 0.008 | 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".