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Record W2048539165 · doi:10.1080/13576500442000292

Attention, reliability, and validity of perceptual asymmetries in the fused dichotic words test

2005· article· en· W2048539165 on OpenAlexaff
Daniel Voyer, Jennifer Ingram

Bibliographic record

VenueLaterality Asymmetries of Body Brain and Cognition · 2005
Typearticle
Languageen
FieldNeuroscience
TopicHemispheric Asymmetry in Neuroscience
Canadian institutionsUniversity of New Brunswick
Fundersnot available
KeywordsDichotic listeningPsychologyStimulus onset asynchronyFree recallPerceptAudiologyRecallStimulus (psychology)PerceptionLateralityCognitive psychologyTone (literature)Developmental psychologyNeuroscienceLinguistics

Abstract

fetched live from OpenAlex

The present experiment investigated the claim that the fused dichotic words test (FDWT) is affected minimally by attentional factors. A total of 40 right-handed undergraduate students were randomly assigned to either a free recall or exogenous cueing condition. In the free recall condition, participants circled on a response sheet the word corresponding to the percept they heard for each trial. In the exogenous cueing condition, a lateralised tone cue was presented with a stimulus onset asynchrony (SOA) of either 150 or 450 ms. Participants responded by circling the word presented to the ear where the tone sounded. Results of the free recall condition showed the expected large right ear advantage (REA). In the exogenous cueing condition, the significant SOA by ear of presentation interaction predicted by an attentional explanation of perceptual asymmetries was obtained. Specifically, the REA obtained at the 150 ms SOA was reduced at the 450 ms SOA for both correct responses and intrusions. These findings suggest that, contrary to claims conveyed in the literature, the FDWT is subject to the influences of attention. This supports the claim that the large and reliable laterality effects obtained with the fused dichotic words test are due in part to a consistent attentional bias.

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)0.002
metaresearch head score (Gemma)0.011
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.385
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.011
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0000.002
Scholarly communication0.0000.001
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 head0.029
GPT teacher head0.279
Teacher spread0.249 · 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

Citations17
Published2005
Admission routes1
Has abstractyes

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