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Record W3131627118 · doi:10.1007/s10902-021-00362-9

Testing Buddha: Is Acute Desire Associated with Lower Momentary Happiness?

2021· article· en· W3131627118 on OpenAlexaboutno aff
Stephen Lee Murphy, Yuka Ozaki, Malte Friese, Wilhelm Hofmann

Bibliographic record

VenueJournal of Happiness Studies · 2021
Typearticle
Languageen
FieldPsychology
TopicMental Health Research Topics
Canadian institutionsnot available
Fundersnot available
KeywordsHappinessPsychologyExperience sampling methodPositive psychologyBuddhismSocial psychologySubjective well-beingPhilosophy

Abstract

fetched live from OpenAlex

Abstract A central Buddhist claim is that having desires causes suffering. While this tenet draws from the belief that an acute desire state is more momentarily aversive than a no-desire state, the efficacy of this belief has yet to be comprehensively examined. To empirically investigate this claim, we furnished data from two experience sampling studies across USA/Canadian ( N = 101; 3224 observations) and Japanese cultures ( N = 237; 8497 observations). We compared states of acute desire with states of no desire regarding momentary happiness. We then tested, in an additional step, whether acute desires at greater conflict with personal goals were associated with even lower levels of momentary happiness. Findings were consistent across studies, with participants experiencing greater momentary happiness when not experiencing a desire compared to experiencing acute desire. Also, the greater the desire conflicted with important goals the lower the momentary happiness. The present findings support a key basis of the Buddhist belief that having desires causes suffering, showing acute desire states on average to be more aversive than no desire states.

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 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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.374
Threshold uncertainty score0.769

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.223
GPT teacher head0.454
Teacher spread0.232 · 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 teacher head, 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

Citations9
Published2021
Admission routes1
Has abstractyes

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