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Record W4308260642 · doi:10.1186/s12978-022-01505-8

Adolescent pregnancy in the time of COVID-19: what are the implications for sexual and reproductive health and rights globally?

2022· editorial· en· W4308260642 on OpenAlexaff
Sylvester Reuben Okeke, Dina Idriss-Wheeler, Sanni Yaya

Bibliographic record

VenueReproductive Health · 2022
Typeeditorial
Languageen
FieldHealth Professions
TopicAdolescent Sexual and Reproductive Health
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsReproductive healthSexual and reproductive health and rightsReproductive medicinePandemicPregnancyPublic healthReproductive rightsMedicineCoronavirus disease 2019 (COVID-19)Environmental healthPolitical sciencePsychologyEconomic growthDevelopmental psychologyPopulationNursingBiology

Abstract

fetched live from OpenAlex

The COVID-19 pandemic has aggravated pre-existing challenges associated with adolescents' sexual and reproductive health and rights (SRHR). Evolving evidence suggest that it could adversely impact the progress made towards improving sexual and reproductive health outcomes among young people. The pandemic has stalled achievements in reducing adolescent pregnancy and child marriage by reinforcing contextual and structural determinants of these reproductive health outcomes, especially among girls. The pandemic has increased disruptions to schooling, decreased access to sexual and reproductive health services and compounded pre-existing socio-economic vulnerabilities. The consequences of neglecting adolescent sexual and reproductive health services over the past 2 years, to focus on COVID-19, continue to emerge. This commentary argues for targeted and responsive approaches to adolescent SRHR that tackle preventable consequences resulting from inequities faced by adolescents globally, particularly girls.

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)0.037
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: Not applicable
GenreCandidate signal: Editorial · Consensus signal: Editorial
Teacher disagreement score0.032
Threshold uncertainty score0.044

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.037
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0030.002
Bibliometrics0.0020.001
Science and technology studies0.0070.005
Scholarly communication0.0100.007
Open science0.0040.003
Research integrity0.0320.036
Insufficient payload (model declined to judge)0.0080.005

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 head0.097
GPT teacher head0.457
Teacher spread0.360 · 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
GenreEditorial

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
Published2022
Admission routes1
Has abstractyes

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