Can a Good Life Be Unsatisfying? Within-Person Dynamics of Life Satisfaction and Psychological Well-Being in Late Midlife
Bibliographic record
Abstract
Psychological investigations into the structure of well-being have been largely cross-sectional. However, longitudinal models are needed as Western societies work to improve individual well-being. The current multilevel-modeling study examined within-person dynamics of well-being over 8 years. I asked two questions: (a) How do life satisfaction and psychological well-being (measures drawn from two well-being research traditions) relate over time? and (b) do these relationships vary on the basis of individuals' extraversion or neuroticism? Measures of life satisfaction and psychological well-being were collected in 8 consecutive years from 159 American adults in late midlife. A dispositional-life-satisfaction set point and yearly variation in life satisfaction both related to higher yearly psychological well-being. Neuroticism, but not extraversion, predicted a stronger within-person relationship between life satisfaction and psychological well-being. For participants with very low neuroticism, life satisfaction and psychological well-being varied independently. In sum, experiences of life satisfaction and psychological well-being converged for more neurotic individuals and diverged for more emotionally stable participants.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".