Relation Between Kaufman Brief Intelligence Test and WISC-III Scores of Children with RD
Bibliographic record
Abstract
Concurrent validity of the Kaufman Brief Intelligence Test (K-BIT) with the Wechsler Intelligence Scale for Children-Third Edition (WISC-III) was evaluated, as well as the K-BIT's accuracy as a predictor of WISC-III scores, in a sample of young children with reading disabilities. The two measures were administered to 65 children from Atlanta, Boston, and Toronto who ranged from 6-5 to 7-11 years of age at testing. Correlations between the verbal, nonverbal, and composite scales of the K-BIT and WISC-III were .60, .48, and .63, respectively. Mean K-BIT scores ranged from 1.2 to 5.0 points higher than the corresponding WISC-III scores. Standard errors of estimation ranged from 10.0 to 12.3 points. In individual cases, K-BIT scores can underestimate or overestimate WISC-III scores by as much as 25 points. Results suggest caution against using the K-BIT exclusively for placement and diagnostic purposes with young children with reading disabilities if IQ scores are required.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".