Assessment of Mental Retardation by School Psychologists
Bibliographic record
Abstract
School psychologists play an important role in the assessment and classification of mental retardation. Although the current diagnostic and classification systems contain slight differences in their diagnostic criteria for mental retardation, they contain three essential elements: (a) a presence of significant deficits in cognitive functioning, (b) a concurrent presence of significant limitations in adaptive behavior, and (c) an onset during the developmental period. Researchers have previously documented the over reliance of IQ testing alone in the diagnosis and classification of mental retardation. We explored the practices and opinions of a random sample of school psychologists regarding the assessment of children for mental retardation. The results of this study reveal that (a) the IQ test results are viewed by many school psychologists as the sole indicator needed to classify a child with mental retardation, (b) 25% of school psychologists surveyed never used a measure of adaptive behavior, and (c) less than half (45%) of psychologists surveyed reported using systematically a standardized measure of adaptive behavior when classifying children with mental retardation. Implications of these findings are discussed.
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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 | 0.002 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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 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".