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Record W2762385870 · doi:10.1177/1077559517733816

Pregnancy and Childbearing Among Young Adults Who Experienced Foster Care

2017· article· en· W2762385870 on OpenAlexaboutno aff
Katie Massey Combs, Stephanie Begun, Deborah Rinehart, Heather N. Taussig

Bibliographic record

VenueChild Maltreatment · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicChild Welfare and Adoption
Canadian institutionsnot available
FundersNational Institute of JusticeNational Institute of Mental HealthNational Institutes of Health
KeywordsYoung adultEducational attainmentPregnancyEthnic groupPsychologyQuarter (Canadian coin)Foster careMedicineDemographyDevelopmental psychologyGerontologyNursingSociology

Abstract

fetched live from OpenAlex

This study explores rates of early pregnancy and parenthood among a sample of young adults ( N = 215), ages 18-22, with a history of foster care. The study also compares the educational attainment, financial resources, and homelessness experiences of young adults who became parents to those who did not. By age 21, 49% of the young women became pregnant, and 33% of young men reported getting someone pregnant. Over a quarter of participants experienced parenthood, which was associated with lower educational attainment, less employment, not having a checking or savings account, and a history of homelessness. Gender moderated the association between parenthood and employment such that males who were parents were more likely than female parents to be employed. Given that these young adults were at risk of early pregnancy and parenthood regardless of emancipation status and across several racial/ethnic groups, the results suggest a need for early pregnancy prevention efforts for all youth with child welfare involvement as well as improving resources and support for those who become young parents.

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)0.001
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 score0.014
Threshold uncertainty score0.028

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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 science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.012
GPT teacher head0.272
Teacher spread0.260 · 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

Citations105
Published2017
Admission routes1
Has abstractyes

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