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Record W2152835264 · doi:10.1080/00224499.2011.565428

Pathways to Early Coital Debut for Adolescent Girls: A Recursive Partitioning Analysis

2011· article· en· W2152835264 on OpenAlexaff
Matthew R. Pearson, Tatyana Kholodkov, James M. Henson, Emily A. Impett

Bibliographic record

VenueThe Journal of Sex Research · 2011
Typearticle
Languageen
FieldPsychology
TopicEating Disorders and Behaviors
Canadian institutionsUniversity of Toronto
FundersEunice Kennedy Shriver National Institute of Child Health and Human Development
KeywordsObjectificationPsychologyHuman sexualityDevelopmental psychologySexual intercourseLongitudinal studyAdolescent developmentClinical psychologyDemographyMedicineGender studiesPopulation

Abstract

fetched live from OpenAlex

This study examined pathways to early coital debut among early to middle adolescent girls in the United States. In a two-year longitudinal study of 104 adolescent girls, recursive partitioning (RP) analyses were conducted to examine the specific factors that were related to engaging in first intercourse by the 10th grade among adolescent girls who had not yet engaged in sexual intercourse by the 8th grade. RP analyses identified subsamples of girls who had low, medium, and high likelihoods of engaging in early coital debut based on six variables (i.e., school aspirations, early physical intimacy experiences, depression, body objectification, body image, and relationship inauthenticity). For example, girls in the lowest likelihood group (3% had engaged in sex by the 10th grade) reported no prior experiences with being touched under their clothes, low body objectification, high aspirations to complete graduate education, and low depressive symptoms; girls in the highest likelihood group (75% had engaged in sex by the 10th grade) also reported no prior experiences with being touched under their clothes, but had high levels of body objectification. The implications of these analyses for the development of female adolescent sexuality, as well as for advances in quantitative methods, are discussed.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.300
Threshold uncertainty score0.521

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.249
GPT teacher head0.434
Teacher spread0.185 · 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 teacher head, 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

Citations32
Published2011
Admission routes1
Has abstractyes

Explore more

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