Bibliographic record
Abstract
After constructing a novel, transaction-level dataset on China’s direct investment into Canada, this paper examines the trends of said foreign direct investment over the past quarter century and places them within the context of their ongoing public policy issues. China’s investment into Canada has a controversial history, in large part due to concerns over China’s state-ownership of the investors. By presenting the scale and forms of this investment, it is possible both to determine what avenues exist to respond to it, and to assess how founded concerns over ownership are. The dataset reveals that China’s investors conducted 783 transactions into Canada for the period 1993 through 2017, for a total of C$86 billion. State-owned investments have played a significant role in China’s investment history in Canada, but have in recent years become less significant than private investment flows from China. Still, the controversy surrounding China’s investment activities continues to draw significant attention, with the result being a need for evidence-based responses to the costs, benefits, risks, and opportunities of said investment. Options for amendments to the Canadian Investment Canada Act are one such avenue to improve the system, but must balance public and international investment concerns, and need to be conducted alongside enhanced investment monitoring policies.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.013 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".