PISA-Ergebnisse für verschiedene AkteurInnen im Bildungswesen: Wege zu einem hohen Leistungsniveau bei gleichzeitig geringer Ungleichheit der Bildungschancen
Bibliographic record
Abstract
PISA (Programme for International Student Assessment) hat mittlerweile einen Bekanntheitsgrad erreicht, der fur eine wissenschaftliche Studie Seltenheitswert hat. Dies ist einerseits der Strategie der OECD zu verdanken, die Studie bewusst in einen bildungspolitischen Kontext zu stellen und die Forschungsfragen an fur die politische Steuerung relevantem Wissen auszurichten und andererseits einer medialen Vereinnahmung in zuweilen kreativer und unterhaltsamer manchmal aber gar reisserischer und plakativer Manier. So sind neue Unterhaltungssendungen entstanden, die sich eng an PISA anlehnen (z.B. «PISA-Landerkampf» in Deutschland oder das Pendant in der Schweiz «Kampf der Kantone»). Auch in anderen Quizsendungen werden gerne Fragen zu PISA gestellt und was gesellschaftlich und politisch brisant ist, findet bald einmal Eingang in die Satire-, Comedie- und Fastnachtsprogramme. (DIPF/Orig.)
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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 | 0.006 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.069 | 0.010 |
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".