Inward foreign investment screening targets China: interdisciplinary perspectives*
Bibliographic record
Abstract
Screening of inward foreign investment in numerous countries worldwide has heightened in recent years for a range of reasons, one of which is the volume of Chinese outward investment. Moulding screening policies around concerns about Chinese investment has been a common pattern, particularly among developed countries and allies of the United States. The application of screening measures to Chinese investments in particular is also seen in recent practice in numerous countries. These developments create potential inconsistencies with international investment law, at least for those countries with an international investment agreement with China. The 2020 arbitral award in Global Telecom v Canada shows that even a provision that explicitly excludes investment screening decisions from a bilateral investment treaty may not apply to prevent all related investment treaty claims. The increased use of screening as a policy tool, with respect to China and otherwise, also raises questions about economic rationale and impact. Put simply, blocking a foreign investment proposal may have negative effects on shareholders, jobs and the economy itself, while even the existence of a restrictive screening regime and the threat of the imposition of conditions on a deal may dampen the appeal for foreign investors.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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 teacher head, 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".