Age differences in the experience of everyday happiness: The role of thinking about the future.
Bibliographic record
Abstract
= 24.6; 68% female; 77% Asian [East Asian, South Asian, and Southeast Asian]; 73% postsecondary educated), combining four data sets collected at two locations (Vancouver, Canada; Hong Kong) with different age samples (older and younger adults). Participants provided up to 30 repeated daily life assessments of momentary affective states and thoughts about the future, over 10 days. Results replicate previous findings by showing that happiness was more strongly associated with low-arousal positive affect and more weakly associated with high-arousal positive affect among older compared to younger adults. Engagement in thinking about the future was higher among younger compared to older adults in general, but its role in moderating the association between happiness and positive affect varying in arousal levels was confounded by the age moderation. Separate analyses conducted for each age group indicate different roles of everyday thinking about the future in shaping happiness experiences for different age groups. Age and future thinking-related contours of happiness are discussed in the context of emotional aging theories. (PsycInfo Database Record (c) 2024 APA, all rights reserved).
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".