The Two Great Healing Traditions: Issues, Opportunities, and Recommendations for an Integrated First Nations Healthcare System in Canada
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The First Nations in Manitoba, Canada, are calling for active recognition and incorporation of holistic traditional healing and medicine ways and approaches by the mainstream healthcare system that has hitherto tended to ignore all but biomedical approaches. This request for recognition requires elaboration on areas of opportunity for collaboration that could positively influence both Indigenous and allopathic medicine. We discuss pathways to an integrated healthcare system as community-based primary healthcare transformation. A community-based participatory research approach was used to engage eight Manitoba First Nations communities. One hundred and eighty-three (183) in-depth, semi-structured key informant interviews were completed in all communities. Grounded theory guided data analysis using NVivo 10 software. We learned that increased recognition and incorporation of traditional healing and medical methods would enhance a newly envisioned funded health system. Elders and healers will be meaningfully involved in the delivery of community-based primary health care. Funding for traditional healing and medicines are necessary components of primary health care. An overall respect for Indigenous health knowledge would aid transformation in community-based primary health care. Recognition of and respect for traditional healing, healers, medicines, therapies, and approaches is also recommended as part of addressing the legacy and intergenerational impact of assimilative policies including Indian residential schools as the Truth and Reconciliation Commission of Canada has stated in its Calls to Action.
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.
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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.020 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it