Bibliographic record
Abstract
Purpose This writing examines the remarkable career of the founding East Asian scholar at Montreal's Concordia University. He was the individual who did more than merely a college professor after 37 years there. He had helped to shape a new course in Sino-Canadian relations. Design This paper will look at an element of soft power engagement between Canada and China before Deng Xiaoping's Open Door Policy. It also examines Concordia's achievement in establishing a China foothold in the early-1980s. Findings Canada has always been a pioneer in engaging Red China. Despite not having formal diplomatic ties until October 1970, Ottawa never abandoned its wish to seek a friendship with Beijing. Amidst the thawing China–Canada relations since 1970, Concordia University recruited a 25-year-old graduate student named Martin Singer to inaugurate its East Asian courses. Singer's auspicious academic career not only gave him to organize Canada's first and the largest student delegation to China but also enabled him to pioneer the first joint-postgraduate studies program between a Chinese and a Western postsecondary institution. He was also a key player in establishing a novel and unique relationship between the PRC and the Western world. Originality This paper provides a glimpse into China's early experience in engaging the world as it left behind decades of communist isolation. It also highlights how serendipities allowed people and institutions to advance in the wake of this exciting period in modern Chinese history.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.026 | 0.013 |
| Scholarly communication | 0.011 | 0.005 |
| Open science | 0.002 | 0.013 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.069 | 0.015 |
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".