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Record W1987255527 · doi:10.1016/j.ijgo.2014.03.009

Origins of the FIGO initiative to reduce the burden of unsafe abortion

2014· article· en· W1987255527 on OpenAlexaffabout
Dorothy Shaw

Bibliographic record

VenueInternational Journal of Gynecology & Obstetrics · 2014
Typearticle
Languageen
FieldMedicine
TopicReproductive Health and Contraception
Canadian institutionsB.C. Women's Hospital & Health CentreBritish Columbia Centre of Excellence for Women's HealthUniversity of British Columbia
Fundersnot available
KeywordsAbortionMedicineUnsafe abortionContext (archaeology)Family planningChristian ministryAbortion lawFamily medicineNursingGynecologyEnvironmental healthPopulationPregnancyPolitical scienceLaw

Abstract

fetched live from OpenAlex

The origins of the International Federation of Gynecology and Obstetrics (FIGO) Initiative for the Prevention of Unsafe Abortion and its Consequences began in 1969 when a young British medical student encountered a young woman in Canada with complications of unsafe abortion. Through evolving understanding of the context of women's lives, including the role of family planning and access to safe abortion globally in preventing the deaths and imprisonment of women, I was able to contribute to FIGO's advocacy through a collaborative initiative with country-led action plans based on a situational analysis. Forty-six member associations rapidly agreed to participate with results of situational analyses-an unprecedented result in FIGO's history. Professor Anibal Faúndes' role has been pivotal to the success of this initiative, including the establishment of a working group of regional coordinators and collaborating agencies to oversee the implementation of action plans involving in-country partners and the Ministry of Health. Deaths from unsafe abortion and its complications are preventable.

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)0.014
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.597
Threshold uncertainty score0.994

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.014
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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 head0.026
GPT teacher head0.332
Teacher spread0.306 · 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.

Study designObservational
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

Citations3
Published2014
Admission routes2
Has abstractyes

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