Bibliographic record
Abstract
加拿大的汉语学习者展现出来的某些规律及汉语教学的一些特点，跟其他环境下的汉语学 习者和汉语教学存在着很多共性。但同时， 加拿大的汉语学习与教学也具有自己的特色。近年来， 国别化研究越来越为学界所重视，这是因为每个国家的语言政策、文化背景、政府与机构的支 持等因素不同，这些因素都会对汉语教学产生影响。 加拿大的多元文化和社会体制尽人皆知。依据加拿大多元法案， "加拿大宪法认可加拿大 公民保留和提升多元文化继承的重要性"；多元文化政策"认可并提升理解多元文化反映加拿大 社会的文化和种族多样性及认可加拿大社会所有成员对保持、提升和分享其文化传承的自由" (Government of Canada, 1985, 3(1)(a))。这种多元文化的理念和政策使人们对继承语的学习持有更 摘要
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.006 | 0.002 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".