Common Examiner Scoring Errors on Academic Achievement Measures
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This study examined the scoring errors across three widely used achievement tests (Kaufman Test of Educational Achievement–Second Edition [KTEA-2], Woodcock–Johnson Tests of Achievement–Third Edition [WJ-III], and the Wechsler Individual Achievement Test–Third Edition [WIAT-III]) by novice examiners. A total of 114 protocols were evaluated for differences between the measures on the frequency and type of scoring errors. Within-measure analyses were also conducted to identify particular composites or subtests that might be more prone to error. Among the three measures, the WIAT-III was found to have the most scoring elements and was, therefore, the measure most susceptible to errors in scoring. Irrespective of the measure, more errors occurred on composites requiring greater examiner inference and interpretation, similar to previous studies on the propensity of scoring errors on cognitive measures. Results are discussed in relation to assessment fidelity and to assessment training practices.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.011 | 0.057 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.000 |
| 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 it