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Record W2014461158 · doi:10.1037/0894-4105.22.3.390

On the perception of sarcasm in dichotic listening.

2008· article· en· W2014461158 on OpenAlexafffund
Daniel Voyer, Andrea Bowes, Cheryl Techentin

Bibliographic record

VenueNeuropsychology · 2008
Typearticle
Languageen
FieldPsychology
TopicCategorization, perception, and language
Canadian institutionsUniversity of New Brunswick
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsDichotic listeningSarcasmPsychologyPerceptionStatement (logic)LateralityActive listeningCognitive psychologySocial psychologyAudiologyCommunicationDevelopmental psychologyLinguisticsNeuroscience

Abstract

fetched live from OpenAlex

The purpose of the present study was to investigate the processing of sincere and sarcastic statements by the cerebral hemispheres. Forty right-handed students were asked to localize sincere and sarcastic statements presented dichotically. Participants either indicated the ear that perceived the sarcastic statement or the ear that perceived the sincere statement in counterbalanced blocks of trials. As expected, results revealed a left ear advantage for sarcastic statements and a right ear advantage for sincere statements. In addition, participants showed faster response time when localizing targets (both sarcastic and sincere) to the left ear compared to the right. Finally, a significant negative correlation between laterality effects in the two tasks provided support for causal hemispheric complementarity. Results are discussed with reference to the contribution of the right and left hemispheres to language processing. Their implications for models of sarcasm perception are also discussed.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
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)0.0030.000

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 head0.029
GPT teacher head0.304
Teacher spread0.274 · 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 source (direct Gemma or distilled Codex), 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

Citations21
Published2008
Admission routes2
Has abstractyes

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