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Record W2904136273 · doi:10.1186/s12992-018-0442-x

Stronger together: midwifery twinning between Tanzania and Canada

2018· review· en· W2904136273 on OpenAlexaffabout
Rachel Sandwell, Deborah Bonser, Emmanuelle Hébert, Katrina Kilroy, Sebalda Leshabari, Feddy Mwanga, Agnes Mtawa, Anne Wilson, Amélie Moritz

Bibliographic record

VenueGlobalization and Health · 2018
Typereview
Languageen
FieldMedicine
TopicGlobal Maternal and Child Health
Canadian institutionsAssociation of Ontario Midwives
FundersFondation Sanofi EspoirSanofi
KeywordsTanzaniaCrystal twinningProfessional associationAssociation (psychology)Public healthSocial policyPolitical scienceMedicineNursingSociologyPublic relationsPsychologyLawSocioeconomics

Abstract

fetched live from OpenAlex

This article describes a twinning relationship between the Canadian Association of Midwives (CAM) and the Tanzania Midwives Association (TAMA). It argues that the twinning relationship strengthened both associations. The article briefly reviews the existing literature on professional associations and association strengthening to demonstrate that professional associations are a vital tool for improving the performance of healthcare workers and increasing their capacity to contribute to national and international policy-making. It then suggests that midwifery associations are particularly significant given the frequent professional marginalization of midwives. The article then describes in depth the relationship between CAM and TAMA, highlighting the accomplishments of the twinned partners, and analyzing the factors that contributed to the success of the relationship. The findings demonstrate that twinning can successfully strengthen associations, increasing their ability to support their membership, care for the public, and shape national policy-making. The article therefore proposes twinning as a successful and cost-effective model for encouraging the growth of the midwifery profession.

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)0.000
metaresearch head score (Gemma)0.000
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: Review · Consensus signal: Review
Teacher disagreement score0.872
Threshold uncertainty score0.914

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.055
GPT teacher head0.366
Teacher spread0.311 · 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
GenreReview

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

Citations19
Published2018
Admission routes2
Has abstractyes

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