Business Tax Reform: More Progress Needed
Bibliographic record
Abstract
In the past 10 years, federal, provincial and territorial governments have adopted several policies to reform business taxation in Canada. Their 2006 budgets have continued in the direction of improving business tax competitiveness, with the most significant rate reductions at the federal level and in the provinces of New Brunswick and Saskatchewan. Such steps are laudable: We can expect a much-needed increase in business investment in coming years as a result. Overall, Canada’s investment in capital stock — non-residential structures and machinery — will be boosted within five years by $45 billion, due to the 2006 changes. There could be a further boost of $90 billion if governments fully implement proposed tax reductions by 2010.1 Given Canada’s poor productivity performance and low capital investment rates, these policy changes are welcome indeed, as they will improve Canadians ’ standard of living. Base-broadening measures that would contribute to a more neutral and efficient business tax regime have been slow to come at both federal and provincial-territorial levels. Quebec has become the most egregious case by re-introducing many targeted regional and industrial credits of questionable effectiveness. Other provinces, such as Ontario, have also been generally using targeted preferences and subsidies rather than looking at broad-based relief. This e-brief documents the historical evolution of business tax policies in Canada since 1997, showing that some good progress has been made at the federal level. Meanwhile, some provinces and territories, especially Ontario, have shown little interest in improving business tax competitiveness. While federal tax cuts boost investment in the provinces, action is required by them as well. Those provinces that have shifted tax structures from investment to other revenue sources
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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 | 0.016 | 0.041 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.005 | 0.005 |
| Scholarly communication | 0.011 | 0.018 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.015 | 0.016 |
| Insufficient payload (model declined to judge) | 0.058 | 0.013 |
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".