Access to Ontario Midwifery Care by Neighbourhood-Level Material Deprivation Quintile, 2006–2017: A Retrospective Cohort Study
Bibliographic record
Abstract
Objective: To describe access to Ontario midwifery care based on socio-economic status.Design: Two retrospective cohort studies.Setting: Ontario, Canada.Participants: (1) All Ontario midwifery billable courses of care discharged between April 1, 2006, and March 31, 2017 (N = 187,009), and (2) all Ontario residents who gave birth (≥ 20 weeks) in Ontario between April 1, 2012, and March 31, 2017 (N = 699,843). Data Sources: The Ontario Midwifery Program Legacy Database and the Better Outcomes Registry & Network’s Ontario perinatal registry.Measurements and Findings: We used residential postal codes to assign socio-economic status quintiles, using the Ontario Marginalization Index’s material deprivation measure. Between 2006 and 2017, the proportion of midwifery clients in the two least-marginalized quintiles was consistently greater than the proportion of midwifery clients in the two most-marginalized quintiles. Between 2012 and 2017, physicians cared for a larger proportion of people in the most-marginalized quintile than midwives, while midwives cared for a larger proportion of people in the least-marginalized quintile. Key Conclusions: People of low socio-economic status in Ontario are less likely to receive midwifery care than people of high socio-economic status. There was little change in this pattern over an 11-year period from 2006 to 2017.Implications: Efforts to reduce inequities in access to midwifery care should be prioritized and will require a multi-pronged approach that is supported by practicing midwives, government, midwifery stakeholder organizations, and other health care professionals. This article has been peer reviewed.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".