Generalizability Theory as Evidence of Concerns About Fairness in Large‐Scale ESL Writing Assessments
Why this work is in the frame
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Bibliographic record
Abstract
Using generalizability theory, this study examined both the rating variability and reliability of English as a second language (ESL) students' writing in two provincial examinations in Canada. This article discusses expected and unexpected similarities and differences related to rating variability and reliability between the two testing programs. As expected, there was more desired but less unwanted variation in ESL and native‐English‐speaking (NES) students' writing scores in Province B than in Province A. But unexpectedly, the results demonstrated systematic differences between ESL and NES students in terms of rating variability. Further, there were lower reliabilities in ESL students' scores in comparison to NES students' scores. These findings raise potential concerns about the fairness of large‐scale ESL writing assessments.
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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 | 0.005 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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 it