A New Logic of Consensus on the Foundations of Science Education in Canada: Results of a Delphi Study of the Expert Community
Bibliographic record
Abstract
Despite episodes of identifiably Canadian influences on science education, the last six decades of science education in Canada has been a decidedly American experience - particularly from the standpoints of: I) the foundational policy documents that have provided explicit impetus to periodic science curriculum reform in Canada; 2) the principal theoretical foundations, guiding assumptions, and goals of science education, and; 3) the development of curricular frameworks in Canadian provincial jurisdictions. Though admittedly contested, it will be argued here that the Canadian systems of science education operating in the provinces and territories have not had opportunity, historically, to engage with curriculum uniquely designed from a Canadian perspective that supplies broad and respected appeal to the context of Canadian society, its demographics, its geographic diversity, and its geopolitical position internationally.
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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 | 0.158 | 0.233 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.033 | 0.031 |
| Scholarly communication | 0.016 | 0.007 |
| Open science | 0.004 | 0.018 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.003 | 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".