Access to Maternal Health Care for Native Canadians on Reserves in Northern Canada
Bibliographic record
Abstract
The history of abuse and isolation of Native Canadian populations has created a gap in maternal health care, resulting in infant mortality rates (IMRs) of 12 per 1000 births for on-reserve populations compared to 5.8 per 1000 births for the general Canadian population. This discrepancy is deemed a population health issue, as Native Canadian people constitute roughly 3% of the Canadian population, but have infant mortality rates similar to other third world countries. Currently, there are multiple government and non-government organizations in charge of providing maternal health care for on-reserve populations. A lack of a unified communication system linking these organizations creates a gap in the delivery of services and compromises the prenatal care in Native Canadians. The current method of caring for high risk pregnancies on Northern Canadian reserves is to fly the mothers out of their home community to a hospital that is both far away from their families and completely foreign to them. This practice contrasts with the cultural norms of the Native Canadian population, where expecting women receive antenatal care from elder women within their community. New models of care, in which midwives are the primary providers of antenatal care within a given community, have recently been implemented in Northern Quebec and other isolated areas of Canada. The midwives work with women elders of the community to provide a full system of maternal care. These new models show great promise in improving our current system of maternal health care for Native Canadians by providing more efficient and accessible antenatal care while also incorporating cultural norms of the communities.
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.
How this classification was reachedexpand
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 | 0.013 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.016 | 0.004 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.003 | 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 itClassification
machine, unvalidatedMachine predicted; both teacher heads agree on what is shown here.
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".