Giving birth in a good way: co-designing culturally safe birthing services with Inuit from Nunavik and their service providers
Bibliographic record
Abstract
BackgroundIndigenous Peoples in remote regions of Canada are routinely transferred outside of their communities for birth -a practice known as childbirth evacuation.Recent evidence links childbirth evacuation with negative health and social impacts.Evacuation affects Inuit in Nunavik (Inuit territory in Northern Quebec), where at least 14% of people leave their communities for birth.Moreover, rapid population growth risks exceeding service capacity for local birthing in the region, recognized for its revitalization of Inuit midwifery and community birthing.With widening inequities in perinatal outcomes between Inuit and non-Indigenous in Quebec, there is a pressing need for culturally safe service re-design of childbirth evacuation, alongside support for continued local birthing in Nunavik. Objectives and methodsThis doctoral project engaged Inuit and their service providers in Montreal and Nunavik to support culturally safe Inuit birth in the context of evacuation and local birthing.Four objectives guided the thesis by publication:Objective 1: Assess the factors and outcomes associated Indigenous childbirth evacuation in Canada as the foundation for stakeholder mobilization and engagement in service re-design, using a scoping review of the literature (addressed in Publication 1).Objective 2: Collate the visions of Inuit evacuated for childbirth and their Montreal service providers about birth in a good way in the context of evacuation, using fuzzy cognitive mapping (FCM) (addressed in Publication 2).Objective 3: Develop a list of priority recommendations, implement, and evaluate these with service providers and Indigenous patient partners at the McGill University Health Centre (Publication 3).Objective 4: Examine Inuit and Nunavik service providers' perspectives on supporting perinatal wellness and birth in a good way in Nunavik, along with pathways for continued childbirth in the region, using FCM (Publication 4).This thesis was conducted in the communities of Nunavik and in Tio'ta:ke (Montreal), the unceded territory of the Kanein:keha'ka nation.As my PhD supervisor, Dr. Neil Andersson provided guidance and support in innovative and meaningful participatory methods, offering generous advice to produce high-quality research.
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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 | 0.016 | 0.021 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.042 | 0.009 |
| Scholarly communication | 0.010 | 0.005 |
| Open science | 0.005 | 0.013 |
| Research integrity | 0.002 | 0.008 |
| Insufficient payload (model declined to judge) | 0.010 | 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".