On the Interrelation of Peer Climate and School Performance in Mathematics: A German-Canadian-Israeli Comparison of 14-Year-Old School Students
Bibliographic record
Abstract
Recent international comparisons of students' scholastic achievement have once again shown enormous worldwide differences in the abilities of youngsters to comprehend text and to solve mathematical problems.The Program for International Student Assessment (PISA) included predominantly countries from the Organization for Economic Cooperation and Development (OECD), among others Germany and Canada.Canada ranked in the top achievement group of the PISA study.The achievement of Germany's students emerged as being in the lowest quarter of all participating countries, and was considerably below the OECD average (Adams & Wu, 2002, Baumeit et al., 2001).These results created a public uproar in Germany, in panicular because they replicated findings of the Third International Mathematics and Science Study (TIMSS) that had been published some years before (Ma1tin et al., 2000;Mullis et al., 2000), and in which Germany, Canada, and Israel had participated.In that study, which was confined to the assessment of mathematics and physics abilities, German students also barely reached the average of all countries paiticipating in it.In this study Canada and Israel had a ranking in the middle group of all panicipating countries as well.
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.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".