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Record W2078795789 · doi:10.1037/1089-2680.8.4.323

Scripts, Transformations, and Suggestiveness of Emotions in Shakespeare and Chekhov

2004· article· en· W2078795789 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

VenueReview of General Psychology · 2004
Typearticle
Languageen
FieldPsychology
TopicEmotions and Moral Behavior
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsScripting languageNarrativeConsciousnessPsychologyHAMLET (protein complex)Folk psychologySocial psychologyEpistemologySociologyAestheticsCognitive psychologyCognitive scienceLiteratureComputer scienceArtPhilosophy

Abstract

fetched live from OpenAlex

Plays are simulations of social interaction that run on minds rather than on computers. Literary simulations depend on folk theory and have 3 properties that are useful to psychology: (a) They offer scriptlike themes and variations that depict narrative progressions with problem-solving motifs, (b) they enable us to experience emotions and their transformations as we try to understand them, and (c) they offer a greater possibility of insight into emotions than do some experiences of everyday life. In Romeo and Juliet, the successions of the script of falling in love are brought to consciousness. In Hamlet, the emotion line engages the audience in the experience of transformations of emotions. In The Seagull, actors depict emotions as giving rise to relationships among characters, with a suggestiveness that engages the audience. Modes of experience enabled by such simulations augment folk theory. The systemic thinking provided by imaginative literature enables us to understand how emotions initiate, maintain, and transform modes of relationship.

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 score0.928
Threshold uncertainty score0.407

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)0.0000.000

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 head0.044
GPT teacher head0.390
Teacher spread0.346 · 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