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Record W2062908667 · doi:10.1080/17470218.2012.715654

Processing of syllables during handwriting: Effects of graphomotor constraints

2012· article· en· W2062908667 on OpenAlexaff
Solen Sausset, Eric G. Lambert, Thierry Olive, Denis Larocque

Bibliographic record

VenueQuarterly Journal of Experimental Psychology · 2012
Typearticle
Languageen
FieldSocial Sciences
TopicWriting and Handwriting Education
Canadian institutionsHEC Montréal
Fundersnot available
KeywordsSyllableHandwritingConstraint (computer-aided design)PsychologyLinguisticsWord (group theory)Mathematics

Abstract

fetched live from OpenAlex

The processing of syllables during the writing of isolated words has been shown to occur either before or during the writing of the word containing them. To demonstrate that this difference is related to graphomotor constraints, participants copied bi- and trisyllabic words three times, in four conditions where graphomotor constraints were gradually increased. As expected, latencies were only affected by syllable number in the low-constraint condition. In all four conditions, interletter intervals at syllable boundaries were longer than intrasyllabic interletter intervals. The difference between inter- and intrasyllabic intervals increased with the level of graphomotor constraint. Taken together, these findings indicate that under low graphomotor-constraint conditions, all the syllable processing takes place prior to the writing of a word, whereas under higher graphomotor-constraint conditions, syllable processing is more sequential, each syllable being processed just before it is written.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.019
GPT teacher head0.370
Teacher spread0.351 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations35
Published2012
Admission routes1
Has abstractyes

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