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Record W23703860 · doi:10.1002/hep.26500

Reading Deficits in Pregnant Teens: Implications for Policy and Practice

2010· article· en· W23703860 on OpenAlexaff
Jessica Menard

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldPsychology
TopicReading and Literacy Development
Canadian institutionsUniversity of Windsor
FundersNational Institute on Alcohol Abuse and Alcoholism
KeywordsReading (process)PsychologyDevelopmental psychologyMedicinePolitical science

Abstract

fetched live from OpenAlex

The present study examined the relationship between teen pregnancy and reading achievement. Girls ages 14 to 17 who were pregnant at the time of testing (n=3) and girls who had never been pregnant (n=19) were compared on measures of reading achievement. Specifically, the WRAT-4 was used to measure lower-order single word reading and spelling skills, and the TOWRE and the NDRT were used to measure higher-order reading fluency and comprehension. A MANOVA was conducted to investigate whether there was a difference between pregnant and never-pregnant teens in one or more domains of reading achievement. Results did not indicate statistically significant differences between groups. Follow-up ANOVAs were conducted to compare pregnant and never-pregnant teens on measures of higher-order reading skills. No differences between groups were noted in any analysis. Due to small sample size, the power of the analyses was limited. Future research should be conducted with a larger sample.

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)0.002
metaresearch head score (Gemma)0.016
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 score0.028
Threshold uncertainty score0.055

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.016
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0110.001

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 head0.037
GPT teacher head0.392
Teacher spread0.355 · 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
Published2010
Admission routes1
Has abstractyes

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