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Factors Influencing Boys' Age at First Intercourse and Condom Use in the Shantytowns of Recife, Brazil

2005· article· en· W2047720390 on OpenAlexaff
Fatima Juárez, Thomas Legrand

Bibliographic record

VenueStudies in Family Planning · 2005
Typearticle
Languageen
FieldHealth Professions
TopicAdolescent Sexual and Reproductive Health
Canadian institutionsUniversité de MontréalUniversité du Québec à Montréal
FundersLondon School of Hygiene and Tropical Medicine
KeywordsCondomSocioeconomic statusSexual intercourseDemographyDeveloped countryDeveloping countryHuman immunodeficiency virus (HIV)Family planningMedicinePopulationEnvironmental healthResearch methodologyFamily medicineSociology

Abstract

fetched live from OpenAlex

Despite the general recognition that the sexual practices of adolescent boys place them at high risk of acquiring sexually transmitted infections (STIs), including HIV, and of causing unwanted pregnancies, advances in mapping their sexual behaviors have been slow. This study uses data recently collected from low-income areas of the city of Recife, Brazil, to study boys' age at first sexual intercourse and factors that hinder their use of condoms. These boys become sexually active at early ages, and despite their general awareness of HIV, they rarely use condoms, especially at ages younger than 15. Sustained family involvement in guiding boys is associated with later first intercourse and an increased use of condoms. Boys who describe themselves as shy with girls have later first intercourse, although the probability of their using condoms does not differ from that of other boys of their age. Higher socioeconomic status leads to earlier sexual activity for boys (in contrast with girls), but also to a greater likelihood of using condoms during first intercourse.

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)0.000
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.229
Threshold uncertainty score0.455

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0000.000
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 head0.417
GPT teacher head0.504
Teacher spread0.087 · 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 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

Citations35
Published2005
Admission routes1
Has abstractyes

Explore more

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