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Record W3169314859 · doi:10.1177/17540739211014946

Operationalizing the Relation Between Affect and Cognition With the Somatic Transform

2021· article· en· W3169314859 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueEmotion Review · 2021
Typearticle
Languageen
FieldPsychology
TopicEmotions and Moral Behavior
Canadian institutionsUniversity of WaterlooUniversity of Guelph
Fundersnot available
KeywordsAffect (linguistics)Complementarity (molecular biology)CognitionOperationalizationPsychologyCognitive psychologyCategorizationRelation (database)Meaning (existential)Social psychologyCognitive scienceCommunicationComputer scienceEpistemologyArtificial intelligence

Abstract

fetched live from OpenAlex

This article introduces the somatic transform that operationalizes the relation between affect and cognition at the psychological level of analysis by capitalizing on the relation between the cognitive-denotative and affective-connotative meaning of concepts as measured with semantic differential rating scales. Following discussion of levels of analysis, the importance of language at the psychological level, and two principles (inextricability and complementarity) summarizing the relation between affect and cognition that are rendered explicit by the somatic transform, we present affect control theory (ACT) and its Bayesian extension (BayesACT) containing the somatic transform. We conclude by identifying examples of inextricability and complementarity in the social science and neuroscience literatures and discussing how our psychological model might be implemented in a realistic neural model.

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.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.932
Threshold uncertainty score0.962

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.059
GPT teacher head0.351
Teacher spread0.292 · 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