Governing birth in a pandemic: A policy analysis of maternity hospital restrictions in Ontario during the COVID-19 pandemic
Bibliographic record
Abstract
Abstract At the beginning of the COVID-19 pandemic, hospitals around the world modified policies for many services, including maternity care, to limit viral transmission. While early decisions were made under significant uncertainty, it is not clear how much consistency there was across jurisdictions, or whether some of these policies inadvertently and disproportionately impacted maternal and infant health for marginalized populations. Using a digital archive database, this study examines how maternity policies evolved during the COVID-19 pandemic across Ontario hospitals, assesses equity implications for marginalized communities, and evaluates the extent to which policy changes aligned with data-driven public health risk assessments. A thematic content analysis of obstetric policy documents on 13 Ontario hospital websites between 2020 and 2023 explores three policy areas with equity implications for maternal care: visitor access, support partner restrictions, and doula care limitations. Using a health equity perspective, findings show a high degree of variability in how the Ontario Ministry of Health policies were implemented both within and across hospitals and raise concerns about equity for marginalized populations, social justice in health, and evidence-informed policy alignment.
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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 | 0.006 | 0.023 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.006 | 0.004 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".