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Record W7036153536

Assessing the economic costs of obstetric evacuation in rural and remote First Nation and Inuit communities in Canada

2023· article· en· W7036153536 on OpenAlexaboutno aff

Bibliographic record

VenueScholarship@Western (Western University) · 2023
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicBotany and Geology in Latin America and Caribbean
Canadian institutionsnot available
Fundersnot available
KeywordsIndigenousFirst nationEconomic costRural areaCost–benefit analysisEconomic impact analysisPublic healthRural healthPregnancy
DOInot available

Abstract

fetched live from OpenAlex

First Nations and Inuit Health Branch guidelines require First Nations and Inuit birthing persons residing on reserve or in rural and remote areas in Canada to travel to urban centres at 36–38 weeks gestational age, to await labour and birth. We sought to determine the costs of obstetric evacuation.\nOur first study was a systematic review identifying obstetric evacuation costs in Canada. Medical evacuation costs, direct and indirect, ranged from $7,714 to $31,794 Canadian dollars. Our second study was a model-based analysis of the cost for fly-in First Nation communities in Ontario. The estimated average cost of obstetric evacuation was $38,551.72 Canadian dollars, comprised of $14,237.44, $8,540.28, $6,564.11, $5,973.01, $2,195.20, $647.92, and $393.76 representing lost productivity, escort, travel, hospitalization, accommodation, meals, and dependents, respectively.\nFuture research could expand our model-based framework to estimate population-level obstetric evacuation costs and conduct economic evaluations of culturally appropriate obstetric services, such as Indigenous midwifery.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.019
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.089
Threshold uncertainty score0.645

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.019
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0040.007
Science and technology studies0.0010.001
Scholarly communication0.0030.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.070
GPT teacher head0.273
Teacher spread0.203 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations0
Published2023
Admission routes1
Has abstractyes

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