Accuracy of Teacher Assessments of Second-Language Students at Risk for Reading Disability
Bibliographic record
Abstract
This study examined the accuracy of teacher assessments in screening for reading disabilities among students of English as a second language (ESL) and as a first language (L1). Academic and oral language tests were administered to 369 children (249 ESL, 120 L1) at the beginning of Grade 1 and at the end of Grade 2. Concurrently, 51 teachers nominated children at risk for reading failure and completed rating scales assessing academic and oral language skills. Scholastic records were reviewed for notation of concern or referral. The criterion measure was a standardized reading score based on phonological awareness, rapid naming, and word recognition. Results indicated that teacher rating scales and nominations had low sensitivity in identifying ESL and L1 students at risk for reading disability at the 1-year mark. Relative to other forms of screening, teacher-expressed concern had lower sensitivity. Finally, oral language proficiency contributed to misclassifications in the ESL group.
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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 | 0.037 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".