Canada: The Intersection of International Achievement Testing and Educational Policy Development
Bibliographic record
Abstract
Canada is the world’s second largest country geographically with a population of just over 35 million people. Canada’s population ranks close to 40th, having less than a half of a percentage point of the world’s population. The country consists of 10 provinces and three territories. Offi cially, Canada is a bilingual country (French and English), although these languages are not equally distributed across the country. New Brunswick is the only offi cial bilingual province, Quebec is considered a Francophone province, and the other provinces are considered to be Anglophone. According to Statistics Canada (2013), there are just over fi ve million students enrolled in Canada’s 15,500 publicly funded schools. There is a small private school system in Canada that services about 8% of eligible students across the country (Ontario Federation of Independent Schools, 2012). Statistics further suggest that the overall population of children in Canada’s schools is slowly but steadily declining.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.011 |
| Science and technology studies | 0.009 | 0.008 |
| Scholarly communication | 0.012 | 0.004 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.021 | 0.003 |
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".