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Record W2085169663 · doi:10.13162/hro-ors.02.02.02

Regulating and Funding Midwifery in Nova Scotia

2014· article· fr· W2085169663 on OpenAlexaffvenueabout
Annie Morrison

Bibliographic record

VenueHealth Reform Observer - Observatoire des Réformes de Santé · 2014
Typearticle
Languagefr
FieldHealth Professions
TopicPrimary Care and Health Outcomes
Canadian institutionsMcGill University
Fundersnot available
KeywordsNova scotiaNova (rocket)Political scienceObstetricsMedicineGeographyEngineeringArchaeologyAeronautics

Abstract

fetched live from OpenAlex

Midwives have been working in Nova Scotia for many years, and midwifery became a government funded and regulated health profession in the province in 2009. Despite the will among many decision-makers in the province to regulate the profession since the mid 1980s, several elections and lack of a management model slowed the program’s development. Implicit goals of having midwifery services included improving the quality of maternal care and health outcomes, keeping up with other provinces, responding to public demand, and saving costs. Strong and persistent bureaucratic and public advocacy work, inter-party collaboration, and research demonstrating positive and safe maternal and newborn health outcomes under midwifery care all had a role in the decision-making process. The implementation responsibility was delegated to three health districts in the province, each being responsible for designing a program to integrate midwives into maternal health care teams. The program has thus far been evaluated in an ad hoc manner with external teams performing comprehensive assessments, though the need for a cost-benefit analysis as well as more systematic assessments has been identified. Though many opportunities exist with midwifery in the province, including a continued high demand for the service, and research demonstrating positive outcomes for mothers and babies, significant challenges and threats remain to be addressed to ensure long-term sustainability of the program. Il y a eu des sage-femmes en Nouvelle-Écosse depuis longtemps, et l’occupation de sage-femme est devenue une profession réglementée et financée par le gouvernement de la province en 2009. Il y avait un intérêt gouvernemental à réguler les sage-femmes depuis les années 1980, mais des élections fréquentes et l’absence d’un modèle d’administration pour le programme ont entravé sa réalisation. Parmi les objectifs implicites à la reconnaissance des services des sage-femmes se trouvaient l’amélioration de la qualité des soins maternels et des résultats de santé maternelle, ainsi que la volonté de ne pas être distancé par les autres provinces, de répondre à la demande du public, et de diminuer les coûts. Le processus de décision a aussi été facilité par une pression constante et forte de la part de la bureaucratie et du public, la collaboration entre les partis politiques, et les résultats de la recherche académique montrant que les soins de sage-femmes produisaient des conditions de sécurité pour les mères et de bons résultats de santé pour les nouveau-nés. La responsabilité d’implémentation du programme a été déléguée à trois juridictions de santé, chacune ayant la responsabilité d’intégrer les sage-femmes dans leurs équipes de soins maternels. Le programme n’a pour l’instant été évalué que de manière parcellaire et ad-hoc par des équipes externes menant des études complètes, mais le besoin d’analyses plus systématiques et d’analyses en coût-bénéfices a été identifié. Bien qu’il existe de nombreuses raisons pour le succès d’un programme de sage-femmes en Nouvelle-Écosse, notamment une forte demande de la part des familles et les résultats de recherche montrant des résultats positifs pour les mères et les bébés, des défis considérables doivent encore être surmontés afin de guarantir la pérennité de ce programme.

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)0.010
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Research integrity
Consensus categoriesResearch integrity
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.252
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0100.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0010.002
Science and technology studies0.0020.001
Scholarly communication0.0000.002
Open science0.0010.001
Research integrity0.0020.003
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 head0.094
GPT teacher head0.397
Teacher spread0.303 · 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; both teacher heads agree on what is shown here.

Study designObservational
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
Published2014
Admission routes3
Has abstractyes

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