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Record W2134661013 · doi:10.1177/00222194030360010601

Cognitive Functioning as Measured by the WISC-R

2003· article· en· W2134661013 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

VenueJournal of Learning Disabilities · 2003
Typearticle
Languageen
FieldPsychology
TopicReading and Literacy Development
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsWechsler Intelligence Scale for ChildrenPsychologyLearning disabilityWechsler Adult Intelligence ScaleDevelopmental psychologyIntelligence quotientCognitionWechsler Preschool and Primary Scale of IntelligencePsychiatry

Abstract

fetched live from OpenAlex

Patterns of performance on the Wechsler Intelligence Scale for Children-Revised (WISC-R) have been proposed as useful tools for the identification of children with learning disabilities (LD). However, most of the studies of WISC-R patterns in children with LD have been plagued by the lack of a typically achieving comparison group, by failure to measure individual patterns, and by the lack of a precise definition of LD. In an attempt to address these flaws and to assess the presence of patterns of performance on the WISC-R, we examined data from 121 children with typical achievement (TA), 143 children with reading disabilities (RD), and 100 children with a specific arithmetic disability (AD), ages 6 to 16 years. The results indicated that the RD and AD groups had significantly lower scores than the TA group on all the Verbal IQ subtests. Many of the children with AD and RD showed a significant difference between Verbal and Performance IQ scores, but so did many of the typically achieving children. Although there were some children with LD who showed the predicted patterns, typically, 65% or more of the children with LD did not. Furthermore, a proportion of the TA group-generally not significantly smaller than that of the RD and AD groups-showed discrepancy patterns as well. Our results indicate that the patterns of performance on intelligence tests are not reliable enough for the diagnosis of LD in individual children. Therefore, it might be more profitable to base the detection of an individual's LD on patterns of achievement test scores.

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)0.002
metaresearch head score (Gemma)0.003
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: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.547
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.003
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 integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.028
GPT teacher head0.309
Teacher spread0.281 · 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