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Record W1976869960 · doi:10.1016/j.ijgo.2007.04.018

Respecting adolescents’ confidentiality and reproductive and sexual choices

2007· article· en· W1976869960 on OpenAlexaff
Rebecca J. Cook, Joanna N. Erdman, Bernard M. Dickens

Bibliographic record

VenueInternational Journal of Gynecology & Obstetrics · 2007
Typearticle
Languageen
FieldMedicine
TopicReproductive Health and Technologies
Canadian institutionsDalhousie UniversityUniversity of Toronto
Fundersnot available
KeywordsConfidentialityAbortionReproductive healthParental consentReproductive rightsInformed consentSexual intercoursePsychologyPregnancyFamily medicineMedicinePopulationPolitical scienceLawEnvironmental healthAlternative medicine

Abstract

fetched live from OpenAlex

Adolescents, defined as between 10 and 19 years old, present a growing challenge to reproductive health. Adolescent sexual intercourse contributes to worldwide burdens of unplanned pregnancy, abortion, spread of sexually transmitted infections (STIs), including HIV, and maternal mortality and morbidity. A barrier to contraceptive care and termination of adolescent pregnancy is the belief that in law minors intellectually mature enough to give consent also require consent of, or at least prior information to, their parental guardians. Adolescents may avoid parental disclosure by forgoing desirable reproductive health care. Recent judicial decisions, however, give effect to internationally established human rights to confidentiality, for instance under the Convention on the Rights of the Child, which apply without a minimum age. These judgments contribute to modern legal recognition that sufficiently mature adolescents can decide not only to request care for contraception, abortion and STIs, but also whether and when their parents should be informed.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.008
metaresearch head score (Gemma)0.018
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.044

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.018
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.007
Scholarly communication0.0030.002
Open science0.0000.003
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0020.000

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 head0.027
GPT teacher head0.348
Teacher spread0.321 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
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

Citations8
Published2007
Admission routes1
Has abstractyes

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