MétaCan
Menu
Back to cohort
Record W4400622092 · doi:10.22374/cjmrp.v12i3.102

A Pilot Project of Collaborative Maternity Education: Understanding Perspectives from Family Medicine and Midwifery

2024· article· en· W4400622092 on OpenAlexaboutno aff
Beth Murray‐Davis, Elizabeth Shaw, Brian Kerley, Sandy Knight

Bibliographic record

VenueCanadian Journal of Midwifery Research and Practice · 2024
Typearticle
Languageen
FieldHealth Professions
TopicPrimary Care and Health Outcomes
Canadian institutionsnot available
Fundersnot available
KeywordsObstetricsMedicineNursingMaternity careMedical educationPolitical scienceHealth care

Abstract

fetched live from OpenAlex

Background: In Canada, the decreasing numbers of family physicians and the small number of midwives providing obstetric care have been associated with a decline in access to maternity services. Several studies and policy documents support the development of models to enhance collaboration between midwives and physicians and to expose trainees to these models. A pilot project was undertaken to implement and evaluate an interprofessional learning opportunity involving midwifery students (MWSs) and family medicine residents (FMRs). Methods: The aim was to describe how FMRs and MWSs develop skills to collaborate, and to identify the feasibility of this type of education. A convenience sample of 12 FMRs and 6 MWSs in a southern Ontario suburban community and their preceptors participated in a series of educational seminars and a clinical placement within the midwifery practice. Qualitative focus groups and interviews were conducted, and data were analyzed using thematic analysis. Results: Qualitative analysis highlighted themes relating to the engaging of learners, logistical challenges, and the perceived value of interprofessional education (IPE).Conclusions: This pilot project highlights barriers to and enablers of IPE. The findings will inform the modification of the project for future use and suggest that this project could be a useful model of IPE for primary maternity care.

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)0.005
metaresearch head score (Gemma)0.006
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.605
Threshold uncertainty score0.982

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0000.000

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 head0.521
GPT teacher head0.585
Teacher spread0.064 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
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
Published2024
Admission routes1
Has abstractyes

Explore more

Same venueCanadian Journal of Midwifery Research and PracticeSame topicPrimary Care and Health OutcomesFrench-language works237,207