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Time Use as a Way of Examining Contexts of Adolescent Development in the United States

2005· article· en· W2317114432 on OpenAlexvenueno aff
Margaret Vernon

Bibliographic record

VenueLoisir et Société / Society and Leisure · 2005
Typearticle
Languageen
FieldSocial Sciences
TopicYouth Development and Social Support
Canadian institutionsnot available
Fundersnot available
KeywordsPsychologyPositive Youth DevelopmentTime-use surveyScreen timeLeisure timeDevelopmental psychologyPaid workTime managementWork (physics)Physical activityMedicine

Abstract

fetched live from OpenAlex

Participation in structured extracurricular activities such as sports, arts, school clubs, and volunteering is associated with higher academic achievement, lower rates of depression, and numerous other positive social-emotional outcomes (Vernon & Jacobs, 2002; Eccles & Barber, 1999). Research has also documented that working at a part-time job after school in adolescence is associated with negative outcomes such as lower school engagement, more drug and alcohol use, and lower life satisfaction (Steinberg, 2002). Researchers have suggested that adolescents who work might have less time for more developmentally beneficial activities (Steinberg & Cauffman, 1995). This paper explores adolescent time use, and particularly how adolescents choose to spend their free time, using data from the American Time Use Survey. The paper compares time use on weekends and weekdays, describes time use by gender and income, and examines differences in time use among adolescents based on their involvement in paid work on the diary day. Adolescents who worked on their diary day did give up time from some other activities, primarily rest and play activities, but they spent similar amounts of time doing homework and attending classes compared with adolescents who did not work on their diary day.

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)0.002
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: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.561
Threshold uncertainty score0.499

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.046
GPT teacher head0.322
Teacher spread0.277 · 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 designQualitative
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

Citations5
Published2005
Admission routes1
Has abstractyes

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