The detrimental effects of obstetric evacuation on Aboriginal women’s health
Bibliographic record
Abstract
In Western society, many colonial practices, such as the removal of Aboriginal women from their communities prior to birth, still detrimentally affects Aboriginal peoples’ lives. Health Canada’s evacuation policy for pregnant Aboriginal women living in rural and remote areas involves nurses, who are employed by the federal government, coordinating the transfer of all pregnant women to urban cities at 36-38 weeks gestational age to await the birth of their baby.1 The policy states that it is founded on concerns for the wellbeing of Aboriginal women, in an attempt to “curb First Nations’ child and maternal mortality rates”.1 However, there is a need to problematize the practice of obstetric evacuation given its colonial roots and its impact on Aboriginal women. The objective of this review paper is to explore and bring awareness to some of the consequences of Canada’s evacuation policy for pregnant Aboriginal women who live in rural and remote regions. Morespecifically, this paper, drawing on ethnographic research previously conducted with Canadian Aboriginal women on their lived experiences of prenatal care and birth, will examine the lack of social support, loss of control, and lack of culturally competent care that Aboriginal women face. The findings demonstrate an urgent need for policy makers to also consider the lived experience of Aboriginal women when making decisions that impact their health.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.005 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| 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".