해외 한국학 진흥을 위한 한국학 강의 방안 : 카나다 UBC의 경우를 중심하여
Bibliographic record
Abstract
본인은 83-83년도에 걸쳐 카나다 밴쿠버에 있는 The University of British Columbia에 파견되어, 이 대학 아시아학과에서 1년간 한국학 강의를 담당한 바 있다. The University of British Columbia가 소재한 Vancouver는 카나다의 광대한 British Columbia주의 남단에 위치한 주요 항구도시일 뿐 아니라, 태평양과 미국으로 연결되는 카나다 서부의 관문이기도 하다. 밴쿠버와 그 주변지역, 즉 Greater Vancouver에는 현재 약 7천명의 한국교포가 이민와서 살고 있으며, 그 수는 매년 증가하는 추세에 있다. The University of British Columbia(이하 UBC라 약칭함)sms British Columbia주의 으뜸가는 대학일뿐 아니라, 카나다 전체에서 손꼽히는 유수한 대학이다. 1915년에 설립되어 오늘날에 이른 UBC에는 현재 2만 5천명의 학생이 있다.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.007 | 0.001 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.005 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.014 | 0.006 |
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; both teacher heads agree on what is shown here.
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".