MétaCan
Menu
Back to cohort
Record W4400616543 · doi:10.22374/cjmrp.v12i2.98

Toward Equity in Access to Midwifery: A Scan of Five Canadian Provinces

2024· article· en· W4400616543 on OpenAlexfundaboutno aff
Laurel Hanson, Deborah Mpofu, Laura Hopkins

Bibliographic record

VenueCanadian Journal of Midwifery Research and Practice · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicCanadian Identity and History
Canadian institutionsnot available
FundersSaskatchewan Health Research Foundation
KeywordsEquity (law)Gender equityObstetricsPolitical scienceGeographyBusinessSocioeconomicsMedicineSociologyGender studies

Abstract

fetched live from OpenAlex

This research project was created to support equitable access to midwifery care for the diverse populations of Saskatchewan women. Given the ongoing implementation and expansion of midwifery across diverse mixes of rural, urban, and aboriginal communities in the health regions of the province, we asked: How can midwifery care be implemented in an equitable and accessible way in Saskatchewan? The first phase of this research explored experiences with midwifery implementation around issues of accessibility through an environmental scan of five Canadian provinces (British Columbia, Manitoba, Ontario, Northwest Territories, and Nova Scotia). By analyzing policy and regulatory documents together with primary data generated through key informant interviews, we discovered an interesting compendium of provincial activities and policies in support of equity to access midwifery. We also identified several important areas in need of strengthening. In this article, we present a brief description of the best practices identified by each province, followed by an exploratory analysis of key thematic issues that are significant in creating equitable access to the full scope of midwifery care. These included funding models, interprofessional relationships, choice of birthplace and second attendants, risk designation, geographic dispersal, community integration, and midwifery human resources.

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)0.009
metaresearch head score (Gemma)0.009
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Scholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.789
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0090.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0050.002
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.244
GPT teacher head0.482
Teacher spread0.238 · 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 designNot applicable
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
Published2024
Admission routes2
Has abstractyes

Explore more

Same venueCanadian Journal of Midwifery Research and PracticeSame topicCanadian Identity and HistoryFrench-language works237,207