Time Use as a Way of Examining Contexts of Adolescent Development in the United States
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".