Dancing with the Dragon: Canadian Investment in China and Chinese Investment in Canada
Bibliographic record
Abstract
While Canadian trade and investment with China is today relatively modest, with China well on track to displace the United States as the world’s largest economy, Canada must make it a priority to prepare for a future characterized by dramatically increased trade and investment between our two countries. This paper sheds light on some the issues and measures Canadian governments will have to consider as they look to establish safe and prosperous relationships with China. To begin with, Canadians choosing to invest in China must be prepared for the risk inherent in that country’s peculiar “capitalism with socialist characteristics.” The Chinese state continues to play an interventionist role in many significant sectors in the economy, and the strategy behind China’s overseas investment in countries such as Canada is specifically aimed at furthering China’s own national security goals and geopolitical influence. Canadians wishing to do business in China will also require great cultural competency. The cultural institution known as guanxi — in which gifts to sway influence are considered an acceptable, even desirable practice — persists in China, with even native Chinese unclear on where to draw the line between “good” guanxi and “bad” corruption. At home, Canadians may soon be forced to confront questions about how much of our own land security and natural resource security we are willing to compromise by permitting Chinese investment to gather up our farmland and key industries. Canadians should decide sooner, not later, how well our own strategic interests are served by permitting unrestricted Chinese investment in our economy. In anticipation of these issues, Canada’s federal and provincial governments should provide increased support for a more comprehensive training and research infrastructure that better prepares Canadians for the growing bilateral trade between our countries. They should also reinvest in the monitoring and regulatory enforcement for food and product safety to ensure that Canadians remain protected from unsafe Chinese imports.
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 | 0.001 | 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 | 0.012 | 0.004 |
| Scholarly communication | 0.007 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 0.000 |
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".