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Record W2626186904

The Influence of Explicit Markers on Slow Cortical Potentials During Figurative Language Processing

2006· article· en· W2626186904 on OpenAlexfundno aff
Todd R. Ferretti, Albert N. Katz, Christopher A. Schwint

Bibliographic record

VenueeScholarship (California Digital Library) · 2006
Typearticle
Languageen
FieldPsychology
TopicLanguage, Metaphor, and Cognition
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsLiteral and figurative languageContext (archaeology)PsychologyLiteral (mathematical logic)Interpretation (philosophy)LinguisticsHistoryPhilosophy
DOInot available

Abstract

fetched live from OpenAlex

Recent event related brain potential (ERP) results show that figurative interpretations of proverbial phrases (e.g., lightning never strikes the same place twice) elicit sustained slow cortical potentials that are more negative over the front of the head than for literal interpretations of the same phrases (Ferretti, Schwint, & Katz, under review).We extend this research by examining the influence of explicit markers placed before the proverbs, such as literally speaking and figuratively speaking, and by contrasting two literal conditions in which there either is overlap or no overlap between content words in the proverbs and the preceding contexts.The results show that slow cortical potentials were most negative for proverbs interpreted in figurative contexts, and most positive for literal contexts that contained overlapping words.Moreover, markers directed readers toward the contextually appropriate interpretation of the proverbs earlier than found in previous research.These findings have direct relevance for theoretical explanations of figurative language processing.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.510
Threshold uncertainty score1.000

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 communication0.0010.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.001

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 head0.008
GPT teacher head0.237
Teacher spread0.229 · 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.

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

Citations2
Published2006
Admission routes1
Has abstractyes

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