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Dimensional models of core affect: a quantitative comparison by means of structural equation modeling

2000· article· en· W2041291477 on OpenAlexaff
Ulrich Schimmack, Alexander Grob

Bibliographic record

VenueEuropean Journal of Personality · 2000
Typearticle
Languageen
FieldPsychology
TopicMental Health Research Topics
Canadian institutionsUniversity of Toronto
FundersDeutsche Forschungsgemeinschaft
KeywordsAffect (linguistics)PleasurePsychologyStructural equation modelingArousalReductionismDimensional modelingCognitive psychologySocial psychologyComputer scienceMathematicsEpistemologyStatisticsCommunicationPhilosophyPsychotherapist

Abstract

fetched live from OpenAlex

The present article compares dimensional models of affect with each other. The article focuses on the pleasure–arousal model, the energetic and tense arousal model, and a three-dimensional model with separate pleasure–displeasure, awake–tiredness, and tension–relaxation dimensions. The results show that the three-dimensional model cannot be reduced to a two-dimensional model. Problems of the two-dimensional models' reductionism are discussed. We conclude that a three-dimensional description of affect is necessary. However, the three-dimensional model is not sufficient to account for all aspects of the structure of affect. Copyright © 2000 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)0.027
metaresearch head score (Gemma)0.077
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.027
Threshold uncertainty score0.144

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0270.077
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.003
Bibliometrics0.0050.005
Science and technology studies0.0010.002
Scholarly communication0.0050.004
Open science0.0020.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0050.000

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 head0.316
GPT teacher head0.461
Teacher spread0.146 · 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 designSimulation or modeling
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

Citations316
Published2000
Admission routes1
Has abstractyes

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