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Record W2062360626 · doi:10.1037/0278-7393.33.2.451

Qualitative differences between the joint effects of stimulus quality and word frequency in reading aloud and lexical decision: Extensions to Yap and Balota (2007).

2007· letter· en· W2062360626 on OpenAlexafffund
Shannon O’Malley, Michael Reynolds, Derek Besner

Bibliographic record

VenueJournal of Experimental Psychology Learning Memory and Cognition · 2007
Typeletter
Languageen
FieldPsychology
TopicReading and Literacy Development
Canadian institutionsUniversity of Waterloo
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsLexical decision taskMental lexiconPsychologyLexiconWord lists by frequencyReading aloudStimulus (psychology)Cognitive psychologyLinguisticsCognitionLexical accessDissociation (chemistry)Word recognitionReading (process)

Abstract

fetched live from OpenAlex

There have been multiple reports over the last 3 decades that stimulus quality and word frequency have additive effects on the time to make a lexical decision. However, it is surprising that there is only 1 published report to date that has investigated the joint effects of these two factors in the context of reading aloud, and the outcome of that study is ambiguous. The present study shows that these factors interact in the context of reading aloud and at the same time replicate the standard pattern reported for lexical decision. The main implication of these results is that lexical activation, at least as indexed by the effect of word frequency, does not unfold in a uniform way in the contexts reported here. The observed dissociation also implies, contrary to J. A. Fodor's (1983) view, that the mental lexicon is penetrable rather than encapsulated. The distinction between cascaded and thresholded processing offers one way to understand these and related results. A direction for further research is briefly noted.

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)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.875
Threshold uncertainty score0.966

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.002
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 head0.093
GPT teacher head0.442
Teacher spread0.349 · 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.

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

Citations34
Published2007
Admission routes2
Has abstractyes

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