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Record W7115806915

Understanding the roles of midwives in political and health systems

2017· dissertation· en· W7115806915 on OpenAlexaboutno aff

Bibliographic record

VenueMacSphere (McMaster University) · 2017
Typedissertation
Languageen
FieldMedicine
TopicMaternal and Perinatal Health Interventions
Canadian institutionsnot available
Fundersnot available
KeywordsCLARITYHealth careQualitative researchHealthcare systemConceptual frameworkSelection (genetic algorithm)Exploratory researchPolitics
DOInot available

Abstract

fetched live from OpenAlex

There is a lack of conceptual clarity regarding the drivers of midwives’ roles within health systems, which has contributed to the significant variability both within and across countries in whether, to what extent and how midwives are integrated in these systems. This dissertation incorporated a mix of methodological approaches to address this gap. First, a critical interpretive synthesis was used to develop a theoretical framework that identifies the different types of policy levers that would be required to enhance to roles of midwives within any given health system, and an exploratory network analysis was used to analyze relationships among the ‘health system arrangements’ part of the framework and to identify gaps in the literature. Second, a logistic regression was used to examine the correlates of birth-experience satisfaction – as a patient experience component of the health system ‘triple aim’ – among women receiving care from midwives, family physicians and/or obstetricians in Ontario’s health system. Third, an embedded single-case study design and Kingdon’s agenda setting and the 3i+E theoretical frameworks were used to qualitatively assess how and under what conditions the Ontario health system has assigned roles to midwives. The research chapters build on each other and make substantive, methodological and theoretical contributions. Specifically, insights gained from the theoretical framework informed variable selection and definition for the quantitative analysis and were tested in the embedded single-case study. Substantively, the dissertation provides a rich understanding of the roles of midwives in health systems through a mix of qualitative and quantitative research evidence, adding to the evidence base that policymakers can draw from when making decisions regarding midwifery care. v Methodologically, the dissertation introduces a novel combination of a critical interpretive synthesis and exploratory network analysis. Lastly, the dissertation advances the theoretical understanding of the roles of midwives within health systems through a new theoretical framework.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.020
metaresearch head score (Gemma)0.023
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.105
Threshold uncertainty score0.258

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0200.023
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0110.041
Scholarly communication0.0150.012
Open science0.0020.008
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0050.000

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 head0.102
GPT teacher head0.334
Teacher spread0.232 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
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

Citations0
Published2017
Admission routes1
Has abstractyes

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