But Is It Good for Non‐Urban Women's Health? Regionalizing Maternity Care Services in British Columbia*
Bibliographic record
Abstract
La Colombie‐Britannique, comme la plupart des autres provinces ou territoires canadiens, s'est orientée au cours de la dernière décennie vers une régionalisation de ses services de santé. Il en a résulté un glissement dans la planification et la prestation de services du centre vers la périphérie et un accent plus important mis sur la prise de décision locale. Cette étude explore les effets de la régionalisation sur la planification et la prestation de soins en maternitéà l'extérieur des grands centres urbains en Colombie‐Britannique. L'article fait la lumière sur la perception qu'ont les futures mères des répercussions de la régionalisation et établit des comparaisons avec les attentes des artisans de réformes à l'endroit du processus mené par le gouvernement. British Columbia, like most other Canadian provinces and territories, has in the last decade moved towards regionalization of health care services. This process has resulted in a shift in service delivery and planning from the core to the periphery, and a greater emphasis on local control and decision making. This study explores the impact of regionalization on the planning and delivery of maternity care services outside of large metropolitan areas of B.C. The paper sheds light on how birthing women perceive the impact of regionalization and compares this information to reform makers' expectations about the government‐led process.
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.006 | 0.004 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".