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Record W2034651422 · doi:10.1016/s0020-7292(03)00218-2

Safe motherhood: the FIGO initiative

2003· article· en· W2034651422 on OpenAlexaboutno aff
Giuseppe Benagiano, B. Thomas

Bibliographic record

VenueInternational Journal of Gynecology & Obstetrics · 2003
Typearticle
Languageen
FieldMedicine
TopicGlobal Maternal and Child Health
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineAttendanceChildbirthDeveloping countryObstetrics and gynaecologyEconomic growthFamily medicinePregnancy

Abstract

fetched live from OpenAlex

Over the last twenty years the international community-realizing that the tragedy of women dying during pregnancy and in childbirth could no longer be tolerated-launched a series of initiatives aimed at making safe motherhood a cornerstone of health services in all countries. Making pregnancy and delivery safe events is particularly complex, as it involves infrastructural and logistic, as well as technical, issues. Women die because they have no access to skilled personnel during pregnancy and at the time of delivery and because--if an emergency situation arises--they cannot reach a facility where emergency obstetric services are available. FIGO, the International Federation of Obstetrics and Gynecology-as the only global organization representing the Obstetricians of the world-decided some time ago that it could not limit its activities to proposing technical guidelines and debating scientific issues. It had to move into the field and, through its affiliated societies, help change the ability of the multitude of women in the developing world to obtain skilled attendance at birth. In 1997, plans were made to launch activities in five areas where maternal mortality was particularly high: Central America (Guatemala, Honduras, Nicaragua and El Salvador), Ethiopia, Mozambique, Pakistan, and Uganda. Five member societies from the developed world (the American College of Obstetricians and Gynecologists, the Society of Obstetricians and Gynecologists of Canada, the Italian Society of Obstetrics and Gynecology, the Royal College of Obstetricians and Gynecologists of the United Kingdom; and the Swedish Society of Obstetrics and Gynecology) agreed to provide support to their counterparts in these five selected areas. The project is now in its final stage. Results are, by and large, positive, demonstrating that, by motivating health professionals in the field and for a relatively modest financial outlay, more efficient use of existing services could be made in a sustainable fashion to save lives.

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)0.013
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Editorial · Consensus signal: none
Teacher disagreement score0.018
Threshold uncertainty score0.070

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0130.006
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0030.002
Scholarly communication0.0040.002
Open science0.0030.008
Research integrity0.0060.005
Insufficient payload (model declined to judge)0.0180.005

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 head0.022
GPT teacher head0.304
Teacher spread0.282 · 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 designNot applicable
Domainnot available
GenreEditorial

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

Citations29
Published2003
Admission routes1
Has abstractyes

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