Bibliographic record
Abstract
Fifth generation wireless telecommunications technology, commonly referred to as 5G, could provide an important foundation for the future of Saskatchewan's rural areas and the application of advanced technology to industries like agriculture, and long-promised advances in telemedicine. But central to the development of Canada's 5G system is the role that the equipment from the Chinese firm Huawei will play. With the United States lobbying Canada to follow it in banning Huawei from its 5G infrastructure, tensions between Canada and China on this and other fronts require the Canadian government to tread carefully. Where domestic policy and international politics collide, hard choices emerge. The risk assessment currently underway in Canada should guide Canada's decision making on what to do about Huawei and 5G, though the inherent uncertainties in this case ultimately require what could be a costly decision.
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 | 0.008 | 0.028 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.020 | 0.005 |
| Scholarly communication | 0.022 | 0.006 |
| Open science | 0.004 | 0.006 |
| Research integrity | 0.036 | 0.012 |
| Insufficient payload (model declined to judge) | 0.085 | 0.006 |
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".