Understanding the Internationalization of Education and Its Demand for a Business of Knowledge: Emerging Issues and Discussions in Canadian Comparative and International Education
Bibliographic record
Abstract
Abstract This chapter uses two recent Canadian policies to frame and discuss emerging topics in Canadian comparative and international education. The first policy is the Accord on the Internationalization of Education (AIE) (ACDE, 2014) prepared by the Association of Canadian Deans of Education. The second policy is the Canadian government policy on higher education: Canada’s International Education Strategy: Harnessing our knowledge advantage to drive innovation and prosperity (CIES) (Government of Canada, 2014). Given Canada’s traditionally decentralized education system with universities working autonomously, a joint Deans’ Association policy, a federal government policy on education, and the substantially enhanced role of the corporate sector in setting education goals provide a very different and contested context for conducting comparative and international education research. This chapter provides some insight into how Canadian comparative and international education researchers are approaching this context.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.006 | 0.014 |
| Science and technology studies | 0.017 | 0.026 |
| Scholarly communication | 0.018 | 0.006 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.011 | 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".