Everything Is Better Together: Analyzing the Relationship Between Socializing and Happiness in the American Time Use Survey
Bibliographic record
Abstract
Social interaction is robustly linked to happiness, but are all daily activities better with other people, or are some activities more enjoyable in solitude? We utilized data from four waves of the American Time Use Survey (ATUS) to test whether the impact of socializing varied across a comprehensive list of activities. Specifically, we examined the relationship between socializing and happiness across more than 80 daily activities by analyzing 105,766 activity episodes from 41,094 participants. Remarkably, we found that participants consistently rated every common daily activity as more enjoyable when interacting with someone else. Across 297 activity-specific coefficients over the 4 years of analyses (60–85 coefficients per year), only one coefficient was negative. Moreover, every activity was significantly more enjoyable with other people in at least 1 year. These results suggest that whether we are eating, reading, or even cleaning up around the house, happiness thrives in the company of others.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".