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Specific Language Impairments in Children

2004· article· en· W2137979702 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueCurrent Directions in Psychological Science · 2004
Typearticle
Languageen
FieldPsychology
TopicLanguage Development and Disorders
Canadian institutionsWestern University
Fundersnot available
KeywordsSpecific language impairmentPsychologyGrammarPast tenseCognitive psychologyReading (process)PerceptionLinguisticsParallelsPhonologySentence processingSyntaxConnectionismCognitionVerbNeuroscience

Abstract

fetched live from OpenAlex

Theories of specific language impairment (SLI) in children turn on whether this deficit stems from a grammar-specific impairment or a more general speech-processing deficit. This issue parallels a more general question in cognitive neuroscience concerning the brain bases of linguistic rules. This more general debate frequently focuses on past-tense verbs, specifically, whether regular verbs (bake-baked) are encoded as rules, and whether irregular forms (take-took) are processed differently. Children with SLI have difficulties with past tenses, so SLI could represent an impairment to rules. An alternative theory explains past-tense deficits in SLI as resulting from a phonological deficit. Evidence for this theory has been obtained from connectionist models of past-tense impairments and from behavioral studies of language- and reading-impaired children. The data suggest that SLI is not an impairment to linguistic rules, that past-tense impairments can be explained as resulting from a perceptual deficit, and that a single processing mechanism is ideally suited to account for these children's difficulties.

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.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.232
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.003
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.027
GPT teacher head0.401
Teacher spread0.375 · 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