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Record W2055044226 · doi:10.1016/s0020-7292(03)00185-1

The role of professional associations in reducing maternal mortality worldwide

2003· review· en· W2055044226 on OpenAlexaff
Jean Chamberlain, R. J. McDonagh, André B. Lalonde, Sabaratnam Arulkumaran

Bibliographic record

VenueInternational Journal of Gynecology & Obstetrics · 2003
Typereview
Languageen
FieldMedicine
TopicGlobal Maternal and Child Health
Canadian institutionsThe Society of Obstetricians and Gynaecologists of CanadaMcMaster University
Fundersnot available
KeywordsMedicineProfessional associationShadow (psychology)Maternal deathTragedy (event)Developing countryMaternal healthProfessional developmentInfant mortalityPregnancyHealth professionalsNursingEnvironmental healthEconomic growthHealth careObstetricsPopulationMedical educationHealth servicesPsychiatry

Abstract

fetched live from OpenAlex

The death of hundreds of thousands of women due to pregnancy-related complications casts a shadow over the modern obstetrical world. This paper examines the potential roles and responsibilities of professional obstetrical and midwifery associations in addressing this tolerated tragedy of maternal deaths. We examine the successes and challenges of obstetrical and midwifery associations and encourage the growth and development of active associations to address maternal mortality within their own borders. Professional associations can play a vital role in the reduction of maternal mortality worldwide. Their roles include lobbying for women's health and rights, setting standards of practice, raising awareness and team building. Associations from developed countries can influence and strengthen their colleagues within developing countries; for example, the FIGO Save the Mothers initiative. Professional associations should be encouraged to play an active role in reducing maternal mortality within their own country and abroad.

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)0.001
metaresearch head score (Gemma)0.004
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 score0.918
Threshold uncertainty score0.644

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.031
GPT teacher head0.383
Teacher spread0.351 · 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

Citations64
Published2003
Admission routes1
Has abstractyes

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