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Record W4225256073 · doi:10.1080/22423982.2022.2071410

Returning childbirth to Inuit communities in the Canadian Arctic

2022· review· en· W4225256073 on OpenAlexafffundabout
Erika Lee, Bryarre Gudmundson, Josée G. Lavoie

Bibliographic record

VenueInternational Journal of Circumpolar Health · 2022
Typereview
Languageen
FieldHealth Professions
TopicIndigenous Studies and Ecology
Canadian institutionsUniversity of Manitoba
FundersCanadian Institutes of Health Research
KeywordsStaffingChildbirthCircumpolar starThe arcticArcticHealth careGeographyNursingPolitical scienceMedicinePregnancyLaw

Abstract

fetched live from OpenAlex

While Inuit living in Nunavut have been advocating for decades for the return of birthing to their own communities, over two-third of births continue to occur outside of the territory. We conducted a literature review to answer the question, why has birthplace choice not been given back to Inuit yet. Based on our review we identified a number of factors impacting birthplace choice, including the organisation of the Nunavut medical system that is focused on primary health care and that cannot easily accommodate the potential clinical risks Western health care associates with birthing, often in isolation from socio-cultural risks; staffing vacancies and turn over in Nunavut, which creates challenges in continuity of care and in maintaining trust; and trends in Canada towards the medicalisation of birthing, which resulted in the displacement of traditional midwifery, and lately in the professionalisation of midwifery with training centres mostly located outside of Nunavut. We recognise that providing more options to birth in the north is complex. While birthing in the north as an option is a given objective, operationalising this objective in a consistent manner is likely going to be a challenge for years to come.

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)0.002
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.310
Threshold uncertainty score0.623

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.006
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.005
Science and technology studies0.0020.001
Scholarly communication0.0030.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.139
GPT teacher head0.465
Teacher spread0.327 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations13
Published2022
Admission routes3
Has abstractyes

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