Rating Scale Assessment of Attention-Deficit/Hyperactivity Disorder (ADHD) and Oppositional Defiant Disorder (ODD): Is there a Normal Distribution and Does it Matter?
Bibliographic record
Abstract
A behavior rating scale for evaluating both exceptionally high and exceptionally low levels of ADHD and ODD symptoms was developed. Mothers, fathers, and teachers in seven elementary schools completed ratings. Resulting data were psychometrically sound, with high internal consistency and test-retest reliability and evidence of factorial, convergent, and discriminant validity. About 25% of children were rated by mothers, fathers, and teachers as having lower than average levels of ADHD, and about 50% were rated as having lower than average ODD symptoms. Children with moderate and severe levels of ADHD and ODD differed from other children on measures of symptom impairment, need for treatment, quality of teacher-student relationship, and peer nominations. Children with exceptionally low levels of ADHD and ODD differed from children with average levels of ADHD and ODD on teacher-completed measures but less so on peer-completed measures. Advantages of evaluating both lower and higher levels of ADHD and ODD 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 | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".