Up, not down: The age curve in happiness from early adulthood to midlife in two longitudinal studies.
Bibliographic record
Abstract
Happiness is an important indicator of well-being, and little is known about how it changes in the early adult years. We examined trajectories of happiness from early adulthood to midlife in 2 Canadian longitudinal samples: high school seniors followed from ages 18-43 and university seniors followed from ages 23-37. Happiness increased into the 30s in both samples, with a slight downturn by age 43 in the high school sample. The rise in happiness after high school and university remained after controlling for important baseline covariates (gender, parents' education, grades, self-esteem), time-varying covariates known to be associated with happiness (marital status, unemployment, self-rated physical health), and number of waves of participation. The upward trend in happiness runs counter to some previous cross-sectional research claiming a high point in happiness in the late teens, decreasing into midlife. As cross-sectional designs do not assess within-person change, longitudinal studies are necessary for drawing accurate conclusions about patterns of change in happiness across the life span.
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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 | 0.006 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| 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".