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Record W3024550065

ADOPTION LAW, DILEMMAS, ATTITUDES AND BARRIERS TO ADOPTION AMONG INFERTILITY PATIENTS IN ISRAEL.

2015· article· en· W3024550065 on OpenAlexaboutno aff
Amira Daher, Yaakov Rosenfeld, Lital Keinan-Boker

Bibliographic record

VenuePubMed · 2015
Typearticle
Languageen
FieldMedicine
TopicReproductive Health and Technologies
Canadian institutionsnot available
Fundersnot available
KeywordsFertilityJudaismQuarter (Canadian coin)LawWelfareState (computer science)Religious lawIslamPolitical scienceSociologyDemographyPopulationGeography
DOInot available

Abstract

fetched live from OpenAlex

INTRODUCTION: Israel Adoption Law requires absolute confidentiality. This type of adoption is basically prohibited by Islamic laws and thus creates a conflict between the State's Law and the Qur'an's directives. OBJECTIVE: (1) to study the attitudes and barriers with respect to adoption among Jewish and Muslim couples undergoing fertility treatments. (2) To describe adoption rates of children in Israel's sectors. METHOD: A cross-sectional survey was conducted in fertility clinics among 204 Muslims and Jews treated for infertility. The participants were asked about their attitudes & knowledge concerning adoption. Additionally, national adoption rates, by sector, were retrieved from the Ministry of Welfare. RESULTS: Adoption rates among Jews were higher than among Muslims'. A prolonged period of fertility treatment was more common among Muslims than among Jews. A quarter of the Muslim couples pointed at the conflict between Quran Law and State law as a potential specific barrier. CONCLUSIONS: It is important to deepen the understanding of the barriers against adoption among Muslims who failed fertility treatments, as well as to examine whether the change in State Law will encourage adoption of children among Muslims in Israel.

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)0.002
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 score0.042
Threshold uncertainty score0.333

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.002
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 head0.039
GPT teacher head0.276
Teacher spread0.237 · 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
Published2015
Admission routes1
Has abstractyes

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