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Record W2096035419 · doi:10.1353/hms.2011.0647

Hume’s Science of Emotions: Feeling Theory without Tears

2011· article· en· W2096035419 on OpenAlexvenueno aff
Mark Collier

Bibliographic record

VenueHume studies · 2011
Typearticle
Languageen
FieldPsychology
TopicEmotions and Moral Behavior
Canadian institutionsnot available
Fundersnot available
KeywordsPassionsFeelingPridePsychologyEpistemologyField (mathematics)Dual (grammatical number)Social psychologyCognitionAppraisal theoryPhilosophy

Abstract

fetched live from OpenAlex

We must rethink the status of Hume’s science of emotions. Contemporary philosophers typically dismiss Hume’s account on the grounds that he mistakenly identifies emotions with feelings. But the traditional objections to Hume’s feeling theory are not as strong as commonly thought. Hume makes several important contributions, moreover, to our understanding of the operations of the emotions. His claims about the causal antecedents of the indirect passions receive support from studies in appraisal theory, for example, and his suggestions concerning the social dimensions of self-conscious emotions can help guide future research in this field. His dual-component hypothesis concerning the processing of emotions, furthermore, suggests a compromise solution to a recalcitrant debate in cognitive science. Finally, Hume’s proposals concerning the motivational influences of pride, and the conventional nature of emotional display rules, are vindicated by recent work in social psychology.

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)0.003
metaresearch head score (Gemma)0.009
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.007
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.009
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0020.025
Scholarly communication0.0070.014
Open science0.0010.003
Research integrity0.0040.007
Insufficient payload (model declined to judge)0.0040.001

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 head0.219
GPT teacher head0.418
Teacher spread0.199 · 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 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

Citations10
Published2011
Admission routes1
Has abstractyes

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