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Record W4401550825 · doi:10.1080/19371918.2024.2383690

Pubertal Development and Pregnancy Outcomes Among System-Involved Youth

2024· article· en· W4401550825 on OpenAlexaboutno aff
Nadine Finigan‐Carr, Jessica Duncan Cance, Rochon K. Steward, Tonya Johnson

Bibliographic record

VenueSocial Work in Public Health · 2024
Typearticle
Languageen
FieldHealth Professions
TopicAdolescent Sexual and Reproductive Health
Canadian institutionsnot available
FundersDepartment of Health and Social CareNational Institute for Health and Care Research
KeywordsNeglectPregnancyLogistic regressionOddsIntervention (counseling)DemographySexual abusePopulationTeenage pregnancyMedicineReproductive healthPositive Youth DevelopmentQuarter (Canadian coin)Odds ratioPsychologyDevelopmental psychologyGerontologyPoison controlSuicide preventionPsychiatryEnvironmental health

Abstract

fetched live from OpenAlex

System-involved youth are a vulnerable population at high-risk of experiencing numerous sexual reproductive health (SRH) outcomes. They are likely to have several risk factors for teen pregnancy and parenting including abuse and neglect histories, lack of a supportive consistent adult in their lives, and limited opportunities to experience normal romantic relationships. Issues of pubertal development are rarely addressed in this population. Data is from system-involved adolescents (n = 301) enrolled in a SRH intervention. The final analysis is restricted to those who were sexually active at baseline (n = 229). Most participants were African Americans between 13–21 years of age. More than 70% reported an early mean age of first sex. Approximately a quarter self-reported early pubertal development. Logistic regression was utilized to examine the odds of pregnancy in relation to self-reported pubertal timing. The findings support the need to develop programming for system-involved youth which address their unique needs.

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)0.001
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 score0.012
Threshold uncertainty score0.023

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.198
GPT teacher head0.426
Teacher spread0.228 · 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

Citations0
Published2024
Admission routes1
Has abstractyes

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