The Hedonic and Eudaimonic Motives for Activities (HEMA) in Japan: The pursuit of well-being
Bibliographic record
Abstract
Hedonia (seeking pleasure and relaxation) and eudaimonia (seeking to improve oneself in congruence with one's values) uniquely contribute to well-being. The authors developed and tested the construct validity of a Japanese version of the Hedonic and Eudaimonic Motives for Activities (HEMA) scale that had been originally developed in North America. Drawing on the theoretical and empirical evidence from research on emotion, we proposed that people would pursue well-being in three different directions: pleasure, relaxation, and eudaimonia. In Study 1, we used the original HEMA scale to examine the Japanese attainment of well-being. The results supported the hypothesized three-factor model. Study 2 revealed that the Japanese version of the HEMA scale measured pleasure, relaxation, and eudaimonia. Each of these subscales showed statistically sufficient internal consistency. There was no gender difference in any of these measures. Scores on the scale systematically corresponded with external criterion variables, such as life satisfaction, affect, Ryff's psychological well-being, social support, and lifestyle. Implications for psychological research and public policies that cover the topic of the pursuit of well-being are discussed.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".