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Record W2799413934 · doi:10.5206/uwomj.v86i2.2000

The detrimental effects of obstetric evacuation on Aboriginal women’s health

2017· article· en· W2799413934 on OpenAlexvenueaboutno aff
Ann Marie Corrado

Bibliographic record

VenueUniversity of Western Ontario Medical Journal · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicIndigenous Health, Education, and Rights
Canadian institutionsnot available
Fundersnot available
KeywordsGovernment (linguistics)ColonialismFace (sociological concept)EthnographyEconomic growthHealth careMedicinePolitical scienceNursingSocioeconomicsSociologySocial science

Abstract

fetched live from OpenAlex

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.

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 imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.845
Threshold uncertainty score0.990

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0110.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.010
GPT teacher head0.298
Teacher spread0.288 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designQualitative
Domainnot available
GenreEmpirical

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".

Quick stats

Citations2
Published2017
Admission routes2
Has abstractyes

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