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Record W2156082851 · doi:10.12927/whp.2010.21665

Safe Abortion Services in Nepal: Initial Years of Availability and Utilization

2010· article· en· W2156082851 on OpenAlexvenueno aff
Shyam Thapa, Kasturi Malla, Indira Basnett

Bibliographic record

VenueWorld health & population · 2010
Typearticle
Languageen
FieldMedicine
TopicReproductive Health and Contraception
Canadian institutionsnot available
Fundersnot available
KeywordsAbortionFamily planningUnintended pregnancyMedicineContext (archaeology)Abortion lawReproductive healthFamily medicinePopulationPregnancyEnvironmental healthGeographyResearch methodology

Abstract

fetched live from OpenAlex

INTRODUCTION: Following the liberalization of the very strict Nepalese abortion law in 2002, the first services for safe induced abortion were introduced in 2004 at the nation's largest women's hospital. This paper examines the client profile, the context of demand for services, affordability and satisfaction with services. DATA AND METHODS: Data for the analysis came from a survey of women who presented themselves at the hospital for induced abortion services and subsequently received the services. RESULTS: Based on a survey of 672 clients, the median age was 26, and most women were married with an average of two living children. The majority reported being impregnated by the husband. Nearly three out of five gave their primary reason for termination as already having the number of children desired; another 42% cited finances. About two-thirds made the decision to abort jointly with the male partner. Most were satisfied with the services received and expenses incurred. About two-fifths reported having used a modern contraceptive method at the time the unwanted pregnancy occurred, while 22.6% reported practising either the safe-period or withdrawal methods. CONCLUSION: The clinic has provided affordable, quality abortion services to women in need. Findings also suggest that many areas need services strengthened, including the continued role of the family planning program in preventing unintended pregnancies.

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 score0.199
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.035
GPT teacher head0.380
Teacher spread0.345 · 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

Citations7
Published2010
Admission routes1
Has abstractyes

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