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Dating, sex, and substance use as correlates of adolescents’ subjective experience of age

2006· article· en· W2041953186 on OpenAlexafffund
Kelly Arbeau, Nancy L. Galambos, S. Mikael Jansson

Bibliographic record

VenueJournal of Adolescence · 2006
Typearticle
Languageen
FieldPsychology
TopicChild and Adolescent Psychosocial and Emotional Development
Canadian institutionsUniversity of VictoriaUniversity of Alberta
FundersCanadian Institutes of Health Research
KeywordsPsychologyDevelopmental psychologySubstance useClinical psychology

Abstract

fetched live from OpenAlex

This study examined in a random community-based sample of 664 12-19-year-olds, the relation of subjective experience of age (SEA) with chronological age, dating experience, sexual activity, and substance use. The results revealed a positive linear relation between SEA and chronological age: individuals who were chronologically older felt subjectively older than their actual age. Several possible sources of interindividual differences in SEA were identified. Adolescents who were dating an older partner felt older compared to other dating adolescents. Sexually experienced adolescents felt older than their non-experienced counterparts. Smoking (in boys), higher alcohol use, and higher drug use were also related to an older SEA. These results suggest an increasing discrepancy between SEA and chronological age across the teen years as young people experience the normative changes associated with adolescence. Dating, sexual, and substance use activities may figure importantly in the way that adolescents experience their age.

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)0.004
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 score0.002
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
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 head0.019
GPT teacher head0.273
Teacher spread0.255 · 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

Citations40
Published2006
Admission routes2
Has abstractyes

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