Reforming Ontario’s Property Tax System: A Never-Ending Story?
Bibliographic record
Abstract
This paper reviews the development of property tax policy in the province of Ontario, Canada, over the last two centuries. This review underlines the highly political nature of property tax policy at the local level in the province. Two important realities make the issue highly salient at the provincial level as well. First, since half or more of the property tax collected by any municipality reflects decisions made at higher (regional or provincial) levels of government, and these decisions are often related in no visible or accountable way to matching benefits to the community, one of the key arguments for local property taxation has been – indeed, has always been since at least 1850 – attenuated. Second, many actions of the provincial government, especially since provincial assumption of assessment in 1970 and the explicit linkage of property and provincial income taxes later in that decade, but even more so since a major shift in property tax policy in 1998 have made it clear that it is the province, not the local government, that has both the first and the last say when it comes to property taxes. In Ontario, property tax policy is pre-eminently a provincial rather than a municipal matter not just by law but, and probably more importantly, by repeated provincial assertions of its controlling role with respect to the tax down to all but the very finest details.
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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 | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.012 | 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".