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Record W3166999601 · doi:10.1037/cep0000257

From lollipops to lidocaine: The need for a universal print-to-speech framework.

2021· article· en· W3166999601 on OpenAlexfundno aff
Jacqueline Cummine, Angela Cullum, Daniel Aalto, Tyson Sereda, Cassidy Fleming, Alesha Reed, Amberley Ostevik, Sienna Cashion-Dextrase, Caroline C. Jeffery, William Hodgetts

Bibliographic record

VenueCanadian Journal of Experimental Psychology/Revue canadienne de psychologie expérimentale · 2021
Typearticle
Languageen
FieldPsychology
TopicMultisensory perception and integration
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsLidocaineComputer scienceSpeech recognitionPsychologyCommunicationNeuroscience

Abstract

fetched live from OpenAlex

OBJECTIVE: There is a strong relationship between reading and articulation (Lervåg & Hulme, 2009; Pan et al., 2011). Given the tight coupling of these processes, innovative approaches are needed to understand the intricacies associated with print-speech connections. Here we ran a series of tightly controlled experiments to examine the impact of mouth perturbations on silent reading. METHOD: = 97; E1 = 27; E2 = 32; E3 = 38) completed each of the tasks two times: once with a somatosensory perturbation (lollipop, bite bar, or lidocaine) and once without. RESULTS: For each experiment, a linear mixed effects analysis was run. Overall, we found that the lollipop (E1) and lidocaine (E3) had some specific effects on word recognition (e.g., for "no" responses), particularly in the Spell-LDT, whereas the bite bar (E2) had no effect on word recognition. The picture categorization task was not impacted by any perturbations. CONCLUSION: These findings provide evidence that sensorimotor information is connected to reading. We discuss how these findings advance our understanding of a print-to-speech framework. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.296
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0080.001

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 head0.065
GPT teacher head0.373
Teacher spread0.307 · 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 designNot applicable
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

Citations3
Published2021
Admission routes1
Has abstractyes

Explore more

Same venueCanadian Journal of Experimental Psychology/Revue canadienne de psychologie expérimentaleSame topicMultisensory perception and integrationFrench-language works237,207