Cognitive Functioning as Measured by the WISC-R
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.
Bibliographic record
Abstract
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.
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it