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Record W1983745880 · doi:10.1080/17470218.2013.838686

Basic Processes in Reading Aloud and Colour Naming: Towards a Better Understanding of the Role of Spatial Attention

2013· article· en· W1983745880 on OpenAlexaff
Serje Robidoux, Derek Rauwerda, Derek Besner

Bibliographic record

VenueQuarterly Journal of Experimental Psychology · 2013
Typearticle
Languageen
FieldPsychology
TopicMultisensory perception and integration
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsReading aloudPsychologyReading (process)Cognitive psychologyRead aloudWord identificationLexical accessIdentification (biology)Lexical decision taskLinguisticsWord recognitionCognition

Abstract

fetched live from OpenAlex

Whether or not lexical access from print requires spatial attention has been debated intensively for the last 30 years. Studies involving colour naming generally find evidence that "unattended" words are processed. In contrast, reading-based experiments do not find evidence of distractor processing. One theory ascribes the discrepancy to weaker attentional demands for colour identification. If colour naming does not capture all of a subject's attention, the remaining attentional resources can be deployed to process the distractor word. The present study combined exogenous spatial cueing with colour naming and reading aloud separately and found that colour naming is less sensitive to the validity of a spatial cue than is reading words aloud. Based on these results, we argue that colour naming studies do not effectively control attention so that no conclusions about unattended distractor processing can be drawn from them. Thus we reiterate the consistent conclusion drawn from reading aloud and lexical decision studies: There is no word identification without (spatial) attention.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.881
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 communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.044
GPT teacher head0.349
Teacher spread0.304 · 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 designBench or experimental
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

Citations5
Published2013
Admission routes1
Has abstractyes

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