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Record W1533807810 · doi:10.24452/sjer.28.3.4731

PISA-Ergebnisse für verschiedene AkteurInnen im Bildungswesen: Wege zu einem hohen Leistungsniveau bei gleichzeitig geringer Ungleichheit der Bildungschancen

2006· article· de· W1533807810 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueSwiss Journal of Educational Research · 2006
Typearticle
Languagede
FieldSocial Sciences
TopicEducation Methods and Technologies
Canadian institutionsDiscovery Air (Canada)
Fundersnot available
KeywordsMedicine

Abstract

fetched live from OpenAlex

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.)

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.010
metaresearch head score (Gemma)0.008
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.362
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0100.008
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.004
Science and technology studies0.0020.002
Scholarly communication0.0010.001
Open science0.0030.000
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0040.001

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.

Opus teacher head0.101
GPT teacher head0.469
Teacher spread0.368 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it