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Record W2604371294 · doi:10.12927/whp.2016.25041

Advocacy for International Family Planning: What Terminology Works?

2016· article· en· W2604371294 on OpenAlexvenueno aff
Douglas Huber, Raymond A. Martin, Mona Bormet

Bibliographic record

VenueWorld health & population · 2016
Typearticle
Languageen
FieldMedicine
TopicGlobal Maternal and Child Health
Canadian institutionsnot available
Fundersnot available
KeywordsFamily planningCLARITYTerminologyPublic relationsAbortionPublic healthMeaning (existential)Family planning policyHealth policyPolitical scienceEconomic growthMedicineNursingPopulationPsychologyPregnancyEnvironmental healthEconomics

Abstract

fetched live from OpenAlex

Advocating for international family planning while avoiding miscommunications with politically and religiously conservative policy makers and the public requires care and clarity with language. We find that terms such as "international family planning" are well received when the meaning is clearly explained, such as "enabling couples to determine the number and timing of pregnancies, including the voluntary use of methods for preventing pregnancy - not including abortion - harmonious with their beliefs and values". Family planning also helps reduce abortions - a powerful message for conservative policy makers and the public. We concur with Dyer et al. (2016) that the messenger is important; we find that many of the most effective advocates are religious leaders and faith-based health providers from the Global South. They know and validate the importance of family planning for improving family health and reducing abortions in their communities. "Healthy timing and spacing of pregnancy" is positive language for policy makers, especially when describing the health impact for women and children. Universal access to contraceptive services is emerging as vital for family health and also to help achieve the Sustainable Development Goals (UN 2015). Language on international family planning will evolve, and clarity of meaning will be foundational for effective advocacy.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.465
Threshold uncertainty score0.330

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.044
GPT teacher head0.374
Teacher spread0.330 · 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 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

Citations2
Published2016
Admission routes1
Has abstractyes

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