The legitimation of OECD's global educational governance: examining PISA and AHELO test production
Bibliographic record
Abstract
Although international student assessments and the role of international organisations (IOs) in governing education via an evidence-based educational policy discourse are of growing interest to educational researchers, few have explored the complex ways in which an IO, such as the OECD, gains considerable influence in governing education during the early stages of test production. Drawing on a comparative analysis of the production of two international tests – the Programme for International Student Assessment (PISA) and the Assessment of Higher Education Learning Outcomes (AHELO) – we show how the OECD legitimises its power, and expertise, and defines ‘what counts’ in education. The OECD deploys three mechanisms of educational governance: (1) building on past OECD successes; (2) assembling knowledge capacity; and (3) deploying bureaucratic resources. We argue that the early stages of test production by IOs are significant sites in which the global governance of education is legitimated and enacted.
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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 | 0.028 | 0.060 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.004 | 0.027 |
| Scholarly communication | 0.012 | 0.005 |
| Open science | 0.001 | 0.009 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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".