Kivalliq Inuit women travelling to Manitoba for birthing: findings from the Qanuinngitsiarutiksait study
Bibliographic record
Abstract
BACKGROUND: The Qanuinngitsiarutiksait study aimed to develop detailed profiles of Inuit health service utilization in Manitoba, by Inuit living in Manitoba (approximately 1,500) and by Inuit from the Kivalliq region of Nunavut who travel to Manitoba to access care not available in Nunavut (approximately 16,000 per year). METHODS: We used health administrative data routinely collected in Manitoba for all services provided and developed an algorithm to identify Inuit in the dataset. This paper focused on health services used by Inuit from the Kivalliq for prenatal care and birthing. RESULTS: Our study found that approximately 80 percent of births to women from the Kivalliq region occur in Manitoba, primarily in Winnipeg. When perinatal care and birthing are combined, they constitute one third of all consults happening by Kivalliq residents in Manitoba. For scale, hospitalizations for childbirths to Kivalliq women about to only 5 percent of all childbirth-related hospitalizations in Manitoba. CONCLUSIONS: The practice of evacuating women from the Kivalliq for perinatal care and birthing is rooted in colonialism, rationalized as ensuring that women whose pregnancy is at high risk have access to specialized care not available in Nunavut. While defendable, this practice is costly, and does not provide Inuit women a choice as to where to birth. Attempts at relocating birthing to the north have proven complex to operationalize. Given this, there is an urgent need to develop Inuit-centric and culturally appropriate perinatal and birthing care in Manitoba.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".