DEVELOPMENT AND PEDIATRIC: LEARNING DISABILITYB-39Measuring the Academic Achievement Gap between Americans and Canadians Using the Wechsler Individual Achievement Test-Third Edition
Bibliographic record
Abstract
Objective: Measuring the academic achievement gap between Americans and Canadians using the Wechsler Individual Achievement Test-Third Edition (WIAT-III) Objective: Examine the size and directionality of score differences on the WIAT-III, a comprehensive and widely used test of academic achievement, using American and Canadian norms. Method: 580 college and university students referred to a provincial assessment centre due to a possibility of Learning Disability (LD) or Attention Deficit Hyperactivity Disorder (ADHD) had their WIAT-III raw scores converted to standardized scores using American and Canadian norms provided by the test publisher's scoring program. Mean age of the students was 23.4 (SD = 8.7), 62.4% were female. Results: Differences between mean Canadian and American composite and subtest scores were minimal and directionality was consistent apart from mathematics. Small effect sizes were found for both composite scores and subtest scores. Scores obtained through the two sets of norms were not meaningfully different as 93–99% of the sample remained within +/− 5 points or within the same classification category when considering composite scores. Similar findings, with few exceptions occurred with subtest scores. Conclusion: No meaningful differences occurred between the composite or subtest test scores of a clinically derived sample of individuals scored using both the American and Canadian norms. This is at odds with what Harrison et al (2014, 2015) found for WAIS-IV scores and the test publisher's website statement regarding WAIS-IV Canadian-American discrepancies. Clinically, this suggests that Canadian practitioners can employ WIAT-III American norms for diagnostic purposes as the discrepancy between achievement scores is rarely large enough to alter classification categories.
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.013 | 0.005 |
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".