Canadian budget will constrain future governments
Bibliographic record
Abstract
Significance This is Canada's first balanced budget since the 2008-09 financial crisis, but had been delayed by about two months. This was ostensibly due to the government's need to recalibrate projections after the drop in the price of oil but probably also as a means of creating a more favourable calendar in the run-up to the 2015 general election, scheduled for October 19. Impacts Balancing the budget will allow the federal government to present promised legislation requiring balanced budgets in the future. This will hinder future, less fiscally conservative, governments in implementing their agendas. The government will lower the small business income tax level by 2 percentage points over the next four years. The government's increase in spending on defence and security represents a reversal of the trajectory of recent years.
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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 | 0.009 | 0.034 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.026 | 0.008 |
| Scholarly communication | 0.022 | 0.006 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.008 | 0.010 |
| Insufficient payload (model declined to judge) | 0.067 | 0.009 |
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".