“I would prefer to have my health care provided over a cup of tea any day”: recommendations by urban Métis women to improve access to health and social services in Toronto for the Métis community
Bibliographic record
Abstract
This article reports on recommendations made by urban Métis women for improving access to health and social services in Toronto, Canada. By applying a conversational method, this research followed up with a subgroup of urban Métis women who participated in the Our Health Counts Toronto longitudinal cohort. Métis women ( n = 11) provided holistic and practical recommendations for improving access to health and social services. These recommendations include (a) Métis presence, (b) holistic interior design, (c) Métis specific or informed service space, (d) welcoming reception/front desk, and (e) culturally informed service providers. During the conversations, the women shared positive experiences with an Indigenous-informed midwifery practice called Seventh Generation Midwives Toronto. Examples from the women will be provided of Seventh Generation Midwives Toronto to illustrate how the recommendations may look in practice. This research illustrates that Métis women hold solutions for improving access to health and social services for the Métis community.
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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 | 0.005 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.011 | 0.003 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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; 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".