Towards the development of contextual questionnaires for the PISA for development study
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
The aim of this paper is to describe the technical issues to be addressed in enhancing the Programme for International Student Assessment (PISA) contextual questionnaires instruments for the PISA for Development (PfD) study. We discuss the conceptual framework for the contextual questionnaires used in PISA, describe the evolution of the PISA contextual questionnaires, review the measures used in several other international studies, and consider how the PISA data have been used to address the policy questions relevant to the OECD member countries. This research, alongside discussions with key stakeholders, including those from participating countries, enabled us to identify seven themes in which the PISA contextual questionnaires could be enhanced and made more relevant for low-and middle-income countries: early learning opportunities, language at home and at school, family and community support, quality of instruction, learning time, socioeconomic status, and school resources. We discuss various options for enhancing these measures.
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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 | 0.003 | 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 | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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