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Record W2962878473 · doi:10.1177/1747021819867638

The impact of consonant–vowel transpositions on masked priming effects in Italian and English

2019· article· en· W2962878473 on OpenAlexafffund
Lucia Colombo, Giacomo Spinelli, Stephen J. Lupker

Bibliographic record

VenueQuarterly Journal of Experimental Psychology · 2019
Typearticle
Languageen
FieldPsychology
TopicPhonetics and Phonology Research
Canadian institutionsWestern University
FundersUniversità degli Studi di PadovaNatural Sciences and Engineering Research Council of CanadaOntario Trillium Foundation
KeywordsVowelPsychologyPriming (agriculture)ConsonantLinguisticsAudiologyCommunicationMedicineBiology

Abstract

fetched live from OpenAlex

There are now a number of reports in the literature that transposed letter (TL) priming effects emerge when two consonants are transposed (e.g., caniso-CASINO) but not when two vowels are transposed (e.g., cinaso-CASINO). In the present article, four masked priming lexical decision experiments, two in Italian and two in English, are reported in which TL priming effects involving the transposition of two adjacent consonants (e.g., atnenna-ANTENNA) were contrasted with those involving the transposition of a vowel and an adjacent consonant (e.g., anetnna-ANTENNA), a contrast not directly examined in the previous literature. In none of the experiments was there any indication that the priming effects were different sizes for the two types of transpositions, including Experiment 4 in which a sandwich priming paradigm was used. These results support the assumption of most orthographic coding models that the consonant-vowel status of the letters is not relevant to the nature of the orthographic code. The question of how to reconcile these results with other TL manipulations investigating vowel versus consonant transpositions is 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 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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.891
Threshold uncertainty score0.435

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)0.0000.000

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 head0.016
GPT teacher head0.392
Teacher spread0.376 · 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

Citations12
Published2019
Admission routes2
Has abstractyes

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