The Influence of Explicit Markers on Slow Cortical Potentials During Figurative Language Processing
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".