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Record W2145990230 · doi:10.1002/per.406

Pleasures and subjective well‐being

2001· article· en· W2145990230 on OpenAlexaff
Shigehiro Oishi, Ulrich Schimmack, Ed Diener

Bibliographic record

VenueEuropean Journal of Personality · 2001
Typearticle
Languageen
FieldArts and Humanities
TopicMedia Influence and Health
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsPleasurePsychologySensation seekingExtraversion and introversionFacet (psychology)Life satisfactionSocial psychologyWell-beingHappinessAssociation (psychology)Developmental psychologyPersonalityBig Five personality traitsPsychotherapist

Abstract

fetched live from OpenAlex

In two daily diary studies we examined the moderating role of sensation seeking in the patterns of relations between physical pleasure and life satisfaction. In study 1 (a 52‐day daily diary study), daily physical pleasure was a significantly stronger predictor of daily social satisfaction among high sensation seekers than among low sensation seekers. We extended the finding of study 1 to more general daily satisfaction in study 2 (a 23‐day diary study). The present findings indicate that physical pleasure is associated with daily satisfaction to the degree that one seeks for such an experience. In addition, we tested whether the association between physical pleasure and daily satisfaction would be moderated also by other facets of extraversion and extraversion as a whole. With the exception of the positive emotion facet in study 1, no facet or extraversion as a whole moderated the relation between physical pleasure and daily satisfaction. The present studies show specificity and replicability of the role that sensation seeking plays in understanding the link between daily physical pleasure and daily satisfaction. Copyright © 2001 John Wiley & Sons, Ltd.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.059
GPT teacher head0.264
Teacher spread0.206 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations127
Published2001
Admission routes1
Has abstractyes

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