Grading Policies in Canada and China: A Comparative Study
Bibliographic record
Abstract
The current trend towards globalization, immigration, and internationalization of schools and universities around the world has led to the increased use of grades across educational systems. Given the use of grades for student promotion, mobilization, and admission into educational programs internationally, there is an urgent need to understand how grades are constructed differently in diverse systems of education. This study specifically examines grading policies across two educational contexts – Canada and China – to gain a nuanced understanding of how grades are constructed in these two systems where we see a large fast increase of Chinese students studying at Canadian tertiary institutions. This comparative analysis of Ministry of Education documents within and across these two learning contexts indicates significant differences in policies that guide teacher constructed grades in Canada and China. In Canada, achievement is the primary consideration in the construction of classroom grades, whereas grades in China include considerations of both the learning (i.e., achievement) and the learner (i.e., learning skills and personal dispositions). The findings of the study have significant implications for understanding the validity of grade interpretations across educational systems.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.006 | 0.021 |
| Science and technology studies | 0.009 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 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".