Sources of Bias in Teacher Ratings of Adolescents with ADHD
Bibliographic record
Abstract
Best practice assessment of childhood ADHD includes behavior ratings from multiple sources across multiple environments. However, adolescents in secondary schools interact with several teachers each day, and research has shown that teacher perceptions of the same child can be highly inconsistent. As a result, rating scale data can be equivocal, depending on which teachers are selected. The intent of the present study was two-fold: 1) to assess the consistency between teacher behavior ratings of adolescents with ADHD, and 2) to explore predictors of rater leniency or severity (i.e., sources of bias). Results suggest that interrater reliability within our sample was moderate, consistent with previous research. Further, teacher characteristics, including sex and age, were related to biases on ratings of student hyperactivity-impulsivity. Specifically, women and younger teachers provided significantly more severe ratings on average than did men and older teachers. Implications for the interpretation and statistical norming of ADHD rating scales 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 | 0.035 | 0.170 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| 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".