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Record W2564769293 · doi:10.1136/jfprhc-2015-101383

Curbing publicly-funded family planning services in Iran: who is affected?

2016· article· en· W2564769293 on OpenAlexafffund
Amir Erfani

Bibliographic record

VenueJournal of Family Planning and Reproductive Health Care · 2016
Typearticle
Languageen
FieldMedicine
TopicGlobal Maternal and Child Health
Canadian institutionsNipissing University
FundersSocial Sciences and Humanities Research Council of CanadaNipissing University
KeywordsFamily planningMedicineSocioeconomic statusFertilityPopulationDemographyTotal fertility rateDeveloping countryLogistic regressionEnvironmental healthEconomic growthResearch methodology

Abstract

fetched live from OpenAlex

OBJECTIVE: In response to a persistent low fertility rate in the country, the Supreme Leader of Iran in 2012 called for the shift to pronatalist population policies. Consequently, Iran's Parliament proposed a bill to curb the provision of contraceptive knowledge and services as a solution to raising the country's low fertility rate. This study aimed to investigate which groups of women will be adversely affected if the provision of subsidised contraceptive methods [i.e. sterilisation, intrauterine device (IUD) and injections] is curbed. METHODS: This study used recent data from the 2014 Tehran Survey of Fertility (n=3012) conducted among a representative sample of 3012 married women of reproductive age, and used multinomial logistic regression analysis to identify women with a higher likelihood of using government-funded contraceptive methods. RESULTS: Currently 82% of married women living in Tehran use a contraceptive method. The use of long-acting contraception, namely sterilisation and IUDs, declined from 34% in 2000 to 20% in 2014, and the prevalence of male methods (withdrawal and condoms) increased from 33% to 55% in the same period. Multivariate results showed that women who have a large number of children, want no more children, live in poor districts, and have low education are more likely to use long-acting contraceptive methods than withdrawal and condoms. CONCLUSIONS: Women of low socioeconomic status who want to stop childbearing are the most vulnerable subgroups of the population if the publicly-funded family planning services are curbed.

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)0.000
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 score0.052
Threshold uncertainty score0.664

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 integrity0.0000.001
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 head0.039
GPT teacher head0.342
Teacher spread0.302 · 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

Citations22
Published2016
Admission routes2
Has abstractyes

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