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Record W2104714449 · doi:10.1556/jcep.3.2005.2.5

Evolutionary pre-adaptation and the idea of character in fiction

2005· article· en· W2104714449 on OpenAlexaff
Keith Oatley, Raymond A. Mar

Bibliographic record

VenueJournal of Cultural and Evolutionary Psychology · 2005
Typearticle
Languageen
FieldPsychology
TopicLanguage, Metaphor, and Cognition
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsCharacter (mathematics)NarrativeConversationMetaphorAdaptation (eye)AbstractionCognitive scienceThe ImaginaryAestheticsSociologyPsychologyEpistemologyLinguisticsCommunicationLiteratureArtPhilosophyPsychoanalysis

Abstract

fetched live from OpenAlex

Fiction can be a means of striving towards truths, but in a way that is more abstract than the truths of everyday happenings. We offer a staircase of evolutionary pre-adaptations on which works of literature such as novels and plays depend. These include systems of mirror-neurons, mimetic ritual, conversational language based on actions, narrative structure, metaphor, and imaginary play. These enable the mental simulations that people create when they listen to, or read, stories. We argue that the abstraction of literary character is a sophisticated version of the making of mental models of others that we form routinely in conversation.

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 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 score0.894
Threshold uncertainty score0.273

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 head0.031
GPT teacher head0.315
Teacher spread0.284 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations28
Published2005
Admission routes1
Has abstractyes

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