The U Shape of Happiness Across the Life Course: Expanding the Discussion
Bibliographic record
Abstract
The notion of a U shape in happiness-that well-being is highest for people in their 20s, decreases to its nadir in midlife, and then rises into old age-has captured the attention of the media, which often cite it as evidence for a midlife crisis. We argue that support for the purported U shape is not as robust and generalizable as is often assumed and present our case with the following arguments: (a) Cross-sectional studies are inadequate for drawing conclusions about within-person change in happiness across the life span; (b) cross-sectional evidence with respect to the ubiquity and robustness of the U shape in general levels of happiness and life satisfaction is mixed; (c) longitudinal support for the U shape in happiness and life satisfaction is also mixed; (d) longitudinal research on subjective indicators of well-being other than general levels of happiness and life satisfaction challenges the U shape; (e) when asked to reflect on their lives, older adults tend to recall midlife as one of the more positive periods; and (f) a focus on a single trajectory of well-being is of limited scientific and applied value because it obscures the diversity in pathways throughout life as well as its sources. Understanding happiness across the life course and moving the research field forward require a multidisciplinary, collaborative approach.
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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 | 0.013 | 0.028 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.003 | 0.013 |
| Scholarly communication | 0.006 | 0.014 |
| Open science | 0.004 | 0.007 |
| Research integrity | 0.004 | 0.008 |
| Insufficient payload (model declined to judge) | 0.008 | 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".