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Record W2918633185 · doi:10.1177/1754073918821438

William James on Passion and Emotion: Influence of Théodule Ribot

2019· article· en· W2918633185 on OpenAlexaff
Louis C. Charland

Bibliographic record

VenueEmotion Review · 2019
Typearticle
Languageen
FieldArts and Humanities
TopicHistory of Emotions Research
Canadian institutionsWestern University
Fundersnot available
KeywordsPassionPeriod (music)PsychologyPsychoanalysisEpistemologyAestheticsPhilosophySocial psychology

Abstract

fetched live from OpenAlex

This case study in the history of “passion” and “emotion” is based on the writings of William James. James is famous for his (1884) theory of emotion. However, like his illustrious colleague, Théodule Ribot, he also recognized the importance of “passion” in psychology. That aspect of James’s work is underappreciated. Ribot explicitly defends the necessity of including “passion” in psychology. James does not go that far. But he does utilize a very similar concept in connection with the term “passion” and there can be little doubt he considered it scientifically legitimate. Consequently, like Ribot, James must be considered an exception to historical accounts of this period which describe a transition from “passion” to “emotion” in which “passion” plays no part.

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)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.007
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0040.014
Scholarly communication0.0050.005
Open science0.0010.002
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.0030.001

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 head0.035
GPT teacher head0.283
Teacher spread0.248 · 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 designNot applicable
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

Citations0
Published2019
Admission routes1
Has abstractyes

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