Canadian budget has election aspects
Bibliographic record
Abstract
Significance Freeland acknowledged that a rising deficit following escalated public expenditure during the pandemic means an emphasis on fiscal restraint, but she was still able to raise spending on green technology and healthcare. The budget forms part of the platform on which the Liberals are already preparing to fight a possible early election. Impacts The Canadian nuclear industry will see growth as the government regards it as part of the country’s low-carbon future. The budget reflects Indigenous issues moving down the political agenda, giving way to pressing economic and security concerns. Critical minerals mining will see significant investment under the government’s strategy, increasing opportunities in this sector. Provincial governments will try to extract more unconditional healthcare funding from the federal government. Planned retrenchment and austerity in the public service make strikes this spring much more likely.
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 | 0.007 | 0.029 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.018 | 0.003 |
| Scholarly communication | 0.015 | 0.003 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.012 | 0.012 |
| Insufficient payload (model declined to judge) | 0.103 | 0.017 |
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".