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Record W1993954269 · doi:10.1044/1092-4388(2007/092)

Construction of Graphic Symbol Utterances by Children, Teenagers, and Adults: The Effect of Structure and Task Demands

2007· article· en· W1993954269 on OpenAlexaff
Natacha Trudeau, Ann Sutton, Emmanuelle Dagenais, Sophie de Broeck, Jill P. Morford

Bibliographic record

VenueJournal of Speech Language and Hearing Research · 2007
Typearticle
Languageen
FieldNeuroscience
TopicNeurobiology of Language and Bilingualism
Canadian institutionsUniversité de MontréalCentre Hospitalier Universitaire Sainte-Justine
Fundersnot available
KeywordsUtteranceSymbol (formal)Task (project management)Object (grammar)Contrast (vision)PsychologyLinguisticsCommunicationCognitive psychologyComputer scienceSpeech recognitionArtificial intelligence

Abstract

fetched live from OpenAlex

PURPOSE: This study investigated the impact of syntactic complexity and task demands on construction of utterances using picture communication symbols by participants from 3 age groups with no communication disorders. METHOD: Participants were 30 children (7;0 [years;months] to 8;11), 30 teenagers (12;0 to 13;11), and 30 adults (18 years and above). All participants constructed graphic symbol utterances to describe photographs presented with spoken French stimuli. Stimuli included simple and complex (object relative and subject relative) utterances describing the photographs, which were presented either 1 at a time (neutral condition) or in an array of 4 (contrast condition). RESULTS: Simple utterances lead to more uniform response patterns than complex utterances. Among complex utterances, subject relative sentences appeared more difficult to convey. Increasing the need for message clarity (i.e., contrast condition) elicited changes in the production of graphic symbol sequences for complex propositions. The effects of syntactic complexity and task demands were more pronounced for children. CONCLUSION: Graphic symbol utterance construction appears to involve more than simply transferring spoken language skills. One possible explanation is that this type of task requires higher levels of metalinguistic ability. Clinical implications and directions for further research are 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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.098
Threshold uncertainty score0.298

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.011
GPT teacher head0.317
Teacher spread0.306 · 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 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

Citations34
Published2007
Admission routes1
Has abstractyes

Explore more

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