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Record W2593394310 · doi:10.3138/jcfs.39.2.229

The Factors Associated with Adolescent Marriages and Outcomes of Adolescent Pregnancies in Mardin Turkey

2008· article· en· W2593394310 on OpenAlexvenueno aff
Melikşah Ertem, Günay Saka, Ali Ceylan, Vasfiye Bayram Değer, Serna Çiftçi

Bibliographic record

VenueJournal of Comparative Family Studies · 2008
Typearticle
Languageen
FieldMedicine
TopicGlobal Maternal and Child Health
Canadian institutionsnot available
Fundersnot available
KeywordsFunctional illiteracyDemographyFertilityPopulationMedicineLogistic regressionPsychologySociology

Abstract

fetched live from OpenAlex

This document investigated the factors that influenced the adolescents’ early marriages. This was a cross-sectional study. Married women (n = 871), aged 15-49 years were selected from the records of primary health centers in Mardin, a multicultural city in southeastern Turkey. We compared the demographic and fertility data and the outcomes of first pregnancies of women during the adolescence. Analysis revealed that 56.1% of the women married when they are younger than 19 years old, and their mean age at first marriage was 16.11 ± 1.49 years (min: 11 years). A number of social factors influenced the adolescent marriages; these were: rural origin, women’s illiteracy, father’s illiteracy, and the prevalent language used at home. Multivariate logistic regression analysis showed that the risk for adolescent marriage was 1.79 (1.19-2.71) for rural origin women, 3.71 (2.16-6.38) for women with illiterate fathers, and 3.17 (2.17-4.64) for women that spoke Kurdish at home. Consanguineous marriages and marriages without a woman’s consent were also higher in the adolescent married group. Adolescent marriages for women had higher rates of fertility, stillbirth, and child mortality. The study concluded that not only the education level of women, also the men was an important determinant of adolescent marriage. There were many social factors that influenced the occurrence of adolescent marriages and it was an important factor influencing both mother and child mortality.

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 score0.013
Threshold uncertainty score0.312

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 integrity0.0000.000
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 head0.110
GPT teacher head0.348
Teacher spread0.238 · 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

Citations30
Published2008
Admission routes1
Has abstractyes

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