e-brief Sales Tax Reform in Ontario: The Time is Right By
Bibliographic record
Abstract
Canada’s federal government, since implementing the Goods and Services Tax in 1991, has repeatedly urged the provinces to reform their own antiquated retail sales taxes. New Brunswick, Nova Scotia and Newfoundland and Labrador did so in 1997, by signing on to the Harmonized Sales Tax (HST), which the federal government administers on their behalf.1 Ontario’s economic outlook would much improve if the province now joined in, by eliminating the province’s destructive retail sales tax. The time is right because the province’s need for long-term thinking about how to improve the investment environment, and the outlook for productivity, wages and jobs, has never been clearer. Were Ontario to eliminate its retail sales tax and adopt a fairer value-added tax, such as the GST, construction investment would increase, as would business spending on machinery and equipment. The reason is that the tax burden on business capital investment would drop significantly. Labour productivity would improve, and with it workers ’ wages. The province’s economic potential, including export sales, would improve permanently by half a percentage point – a tremendous boost in provincial income. After discussing the economic benefits of reform, now, in Ontario, this e-brief examines typical objections to reform, including concerns about the speed with which those benefits would flow, the impact of reform on consumer prices and on low-income families as well as particular business sectors. In each case, I outline policy responses that would mitigate the perceived downsides to change. I N
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.008 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.028 | 0.004 |
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".