Age-related invariance of abilities measured with the Wechsler Adult Intelligence Scale-III.
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
Assessment of measurement invariance across populations is essential for meaningful comparison of test scores, and is especially relevant where repeated measurements are required for educational assessment or clinical diagnosis. Establishing measurement invariance legitimizes the assumption that test scores reflect the same psychological trait in different populations or across different occasions. Examination of Wechsler Adult Intelligence Scale-Fourth Edition (WAIS-IV) U.S. standardization samples revealed that a first-order 5-factor measurement model was best fitting across 9 age groups from 16 years to 69 years. Strong metric invariance was found for 3 of 5 factors and partial intercept invariance for the remaining 2. Pairwise comparisons of adjacent age groups supported the inference that cognitive-trait group differences are manifested by group differences in the test scores. In educational and clinical settings these findings provide theoretical and empirical support to interpret changes in the index or subtest scores as reflecting changes in the corresponding cognitive abilities. Further, where clinically relevant, the subtest score composites can be used to compare changes in respective cognitive abilities. The model was supported in the Canadian standardization data with pooled age groups but the sample sizes were not adequate for detailed examination of separate age groups in the Canadian sample. (PsycINFO Database Record
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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 | 0.001 | 0.000 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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