How Robust Are Cross‐Country Comparisons of PISA Scores to the Scaling Model Used?
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
Abstract The Programme for International Student Assessment (PISA) is an important international study of 15‐olds' knowledge and skills. New results are released every 3 years, and have a substantial impact upon education policy. Yet, despite its influence, the methodology underpinning PISA has received significant criticism. Much of this criticism has focused upon the psychometric scaling model used to create the proficiency scores. The aim of this article is to therefore investigate the robustness of cross‐country comparisons of PISA scores to subtle changes to the underlying scaling model used. This includes the specification of the item‐response model, whether the difficulty and discrimination of items are allowed to vary across countries (item‐by‐country interactions) and how test questions not reached by pupils are treated. Our key finding is that these technical choices make little substantive difference to the overall country‐level results.
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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 | 0.001 | 0.002 |
| 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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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