Bibliographic record
Abstract
贝祥大使为贝祥集团的总裁、创始人。他在担任加拿大驻华大使近六年后，结束了其25年的政府工作生涯。期间，他作为加拿大驻华大使经历了加中双边关系的快速发展，亲自参与制定和执行了一系列旨在促进加中关系的决策，包括组织接待了三次由克雷蒂安总理率领的庞大的加拿大“国家队”（Team Canada）访华。之前，贝祥先生曾任加政府内阁国家团结事务副秘书长、加外交部负责亚洲事务的助理副部长、总理APEC私人代表、海湾战争和苏联解体时期的政策规划负责人、加外交部运输政策司负责人和首席航空谈判代表助理；人事处，综合管理司资源管理处处长，北亚关系司处长，政策规划司司长等职。 贝祥先生现任加中贸易理事会（CCBC）副主席、多家公司董事会董事、不列颠哥伦比亚大学（UBC）国际商学院兼职教授。 获麦吉尔大学（McGill）学士和硕士学位，并在多伦多大学及巴黎政治科学国家基金会继续其研究生学习。 前加拿大驻华大使贝祥先生，由一位典型的学者型外交官创立贝祥投资集团初期只从事中国与加拿大投资咨询开始，发展成如今拥有自己基金并将业务拓展到中国大陆、欧美和中亚等国家的投资集团总裁。
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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 | 0.006 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.009 | 0.011 |
| Scholarly communication | 0.017 | 0.013 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.013 | 0.002 |
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".