Provinces blamed for COVID third wave shortcomings
Bibliographic record
Abstract
Significance Some of Canada’s largest provincial governments have seen their approval ratings fall in the wake of the third wave, although there has been little impact on the Liberal government in Ottawa. The political consequences will remain significant in the coming months. Impacts Changes in government could see all provinces except Saskatchewan have a carbon tax in place by 2023. Manitoba could see the election of Wab Kinew as Canada’s first Indigenous provincial premier if current trends continue. Universal pharmacare is off the table for now, as Ottawa and provinces seek to woo back pharmaceutical investment. A return to power of the NDP in Alberta would see several significant mining and oil sands projects cancelled.
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 | 0.016 | 0.058 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.022 | 0.006 |
| Scholarly communication | 0.015 | 0.004 |
| Open science | 0.004 | 0.007 |
| Research integrity | 0.008 | 0.015 |
| Insufficient payload (model declined to judge) | 0.050 | 0.008 |
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".