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Record W4286697523 · doi:10.1080/01490400.2022.2102097

Leisure’s Relationships with Hedonic and Eudaimonic Well-Being in Daily Life: An Experience Sampling Approach

2022· article· en· W4286697523 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueLeisure Sciences · 2022
Typearticle
Languageen
FieldPsychology
TopicFlow Experience in Various Fields
Canadian institutionsUniversity of Alberta
FundersSasakawa Sports Foundation
KeywordsExperience sampling methodEudaimoniaPsychologyMultilevel modelWell-beingSocial psychologyMeaning (existential)Affect (linguistics)Leisure activityDevelopmental psychologyPsychotherapist

Abstract

fetched live from OpenAlex

Research on leisure and subjective well-being has focused on hedonic well-being (e.g., positive affect). Leisure’s relationships with eudaimonic well-being (e.g., meaning) remains underexplored. The literature also lacks non-Western perspectives. This study examined leisure’s relations with shiawase and ikigai, Japanese concepts that represent hedonic and eudaimonic well-being, respectively. A smartphone-based experience sampling method was used. A total of 2,207 responses were collected from 83 Japanese university students. Multilevel linear modeling showed that free time (e.g., lunch, evenings) predicted higher levels of daily shiawase and ikigai, while ikigai appeared to stay higher during afternoon. Various leisure activities positively predicted shiawase and ikigai levels, with event/trip, eating/drinking, socializing, and hobbies being the best predictors. A few activities (e.g., exercise) differentially predicted the outcomes. Among subjective experiences common during leisure, intrinsic motivation, enjoyment, stimulation, and comfort were positively correlated to shiawase and ikigai, whereas effort predicted only ikigai.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.185
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0020.001
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.069
GPT teacher head0.333
Teacher spread0.264 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it