China's Canada spat will damage ties with rest of West
Bibliographic record
Abstract
Subject The impact of China's detentions of two Canadians on the countries relations with Western governments. Significance Two Canadian citizens have been detained in China since December 10 in apparent retaliation for Canada’s arrest of Huawei’s chief financial officer, Meng Wanzhou, on a US extradition request. Beijing says think tank researcher Michael Kovrig and businessman Michael Spavor are suspected of “endangering state security,” but has provided no further details. China’s ambassador in Ottawa has twice made clear that the two men are, in effect, hostages. Their detentions form part of a broader attempt to pressure Canada’s political leaders into intervening in the judicial process concerning Meng, most recently apparent in the re-sentencing of an accused Canadian drug trafficker to death. Impacts The issue will overshadow China-Canada relations for at least as long as the processing of Meng’s extradition. Canada will block Huawei from construction of its 5G mobile network; the United Kingdom will likely follow suit. Washington will find it harder to persuade other governments to agree to its extradition requests for Chinese citizens. Western researchers will be deterred from working in China, making Beijing’s intentions more difficult for Western governments to assess.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.021 | 0.003 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.006 | 0.005 |
| Insufficient payload (model declined to judge) | 0.051 | 0.005 |
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".