Reforming the Federal Fiscal Stabilization Program
Bibliographic record
Abstract
The federal Fiscal Stabilization Program is meant to provide financial support for provinces that suffer extraordinary declines in revenues. However, the program only provided $248 million payment to Alberta in 2015-16 in the face of a $8.8 billion decline in revenues, and no support for Saskatchewan and Newfoundland and Labrador that have also suffered significant revenue reductions in recent years. We discuss the rationale for a Fiscal Stabilization Program, and three principles that should be adopted in re-designing it: · Payments should be based on declines in a province’s own-source revenues from an average of its past years’ own-source revenues · The program should preserve incentives for provinces to maintain prudent fiscal policies by only covering losses that exceed some percentage of “normal” own-source revenues (a deductible) and then only covering a fraction of eligible losses (co-insurance). · Formulas determining payments should be simple and transparent with no adjustment for changes in provincial tax policies that may affect own-source revenues. We propose some alternative formulas, consistent with these principles, for calculating the fiscal insurance payments and show the support levels that they would have provided to the provinces since the mid-1980s.
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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 | 0.024 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".