Bibliographic record
Abstract
This paper exploits the richness and large sample size of the Gallup/Healthways US daily poll to illustrate significant differences in the dynamics of two key measures of subjective well-being: emotions and life evaluations.We find that there is no day-of-week effect for life evaluations, represented here by the Cantril Ladder, but significantly more happiness, enjoyment, and laughter, and significantly less worry, sadness, and anger on weekends (including public holidays) than on weekdays.We then find strong evidence of the importance of the social context, both at work and at home, in explaining the size and likely determinants of the weekend effects for emotions.Weekend effects are twice as large for full-time paid workers as for the rest of the population, and are much smaller for those whose work supervisor is considered a partner rather than a boss and who report trustable and open work environments.A large portion of the weekend effects is explained by differences in the amount of time spent with friends or family between weekends and weekdays (7.1 vs. 5.4 hours).The extra daily social time of 1.7 hours in weekends raises average happiness by about 2%.
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 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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".