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Record W2102500724 · doi:10.1017/s136672890700288x

The universality of symbolic representation for reading in Asian and alphabetic languages

2007· article· en· W2102500724 on OpenAlexaffabout
Ellen Bialystok, Gigi Luk

Bibliographic record

VenueBilingualism Language and Cognition · 2007
Typearticle
Languageen
FieldPsychology
TopicReading and Literacy Development
Canadian institutionsYork University
Fundersnot available
KeywordsLearning to readReading (process)Universality (dynamical systems)CognitionWriting systemLiteracySimilarity (geometry)Representation (politics)LinguisticsTask (project management)PsychologyPoint (geometry)Cognitive psychologyComputer scienceArtificial intelligencePoliticsMathematics

Abstract

fetched live from OpenAlex

Neuroimaging studies of reading have identified unique patterns of activation for individuals reading in alphabetic and Asian languages, suggesting the involvement of different processes in each. The present study investigates the extent to which a cognitive prerequisite for reading, the understanding of the symbolic function of print, is common to children learning to read in these two different systems. Four-year-old children in Hong Kong learning to read in Cantonese and children in Canada learning to read in English are compared for their understanding of this concept by means of the moving word task. Children in both settings performed the same on the task, indicating similar levels of progress in spite of experience with very different writing systems. In addition, the children in Hong Kong benefited from the structural similarity between certain iconic characters and their referents, making these items easier than arbitrary characters. These results point to an important cognitive universal in the development of literacy for all children that is the foundation for skilled reading that later becomes diverse and specialized.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.721
Threshold uncertainty score0.209

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.357
Teacher spread0.340 · 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 designOther design
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

Citations19
Published2007
Admission routes2
Has abstractyes

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