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 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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.008 | 0.007 |
| Scholarly communication | 0.008 | 0.005 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.041 | 0.005 |
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".