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Record W4323521532 · doi:10.7202/1097019ar

THE HEDONIST’S EMOTIONS

2023· article· en· W4323521532 on OpenAlexvenueno aff
Julien Deonna, Fabrice Teroni

Bibliographic record

VenueLes ateliers de l éthique · 2023
Typearticle
Languageen
FieldPsychology
TopicEmotions and Moral Behavior
Canadian institutionsnot available
Fundersnot available
KeywordsHedonismPleasureHappinessIntuitionVariety (cybernetics)EudaimoniaValue (mathematics)PsychologyEpistemologyConstraint (computer-aided design)Affect (linguistics)Social psychologyAestheticsPhilosophyComputer scienceCommunication

Abstract

fetched live from OpenAlex

This paper explores the compelling hedonistic intuition that emotions affect happiness because they are states of pleasure and displeasure . The discussion focusses on two constraints on a plausible version of hedonism and explains which accounts of the emotions satisfy these constraints. Section 1 revolves around the nonalienation constraint : the constituents of a subject’s happiness must engage him or her. We argue that the intuition that emotions have prudential value presupposes that emotions are forms of engagement, a condition that only some accounts of the emotions satisfy. Section 2 centres around the unity constraint : if we acknowledge a great variety of (dis)pleasures, we still need to understand what makes all of them (dis)pleasures. Conceiving of the emotions as forms of engagement, we contend, allows us to resolve the difficulties concerning the variety and unity of (dis)pleasures that weigh on traditional hedonism. In section 3, we defend the form of affective hedonism that has emerged. We argue that the approach can be extended from emotions to other affective states and that the central role we give to action tendencies in our conception of affectivity does not call into question the idea that emotions contribute to happiness because of their hedonic value.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.734
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.002

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 head0.045
GPT teacher head0.345
Teacher spread0.300 · 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.

Study designTheoretical or conceptual
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

Citations1
Published2023
Admission routes1
Has abstractyes

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