Tax Payers and Tax Takers: Is the Trend of Tax Progressivity in the US Emerging in Canada?
Bibliographic record
Abstract
The traditional definition of tax progressivity is being rewritten and this change could have serious ramifications for democratic decision-making. Up to now, tax progressivity has meant that, as an individual or household earned more income, they not only paid more in taxes but also paid a proportionately higher share of their income in taxes. The concept of tax progressivity is being fundamentally altered by government’s expansion of eligibility for tax credits that were initially targeted at low-income earners. The result is that rather than a progressively increasing tax burden, there is a fairly large and growing group of people who do not contribute to taxes in any meaningful way and another group of people, fairly small, that carry the overwhelming burden of taxes.The new tax progressivity is not yet as pronounced in Canada as it is in the United States, but it has gained an entrance and there is a possibility of its expanding rapidly. If the benefits of tax credits like Canada’s Working Income Tax Benefit (WITB) and the United States’ Earned Income Tax Credit (EITC), continue to increase and their application expands to an even wider group of citizens, this program, coupled with others like Canada’s Child Tax Credit (CTC), may very well lead to a tax distribution similar to that observed in the United States today, where a growing number of households pay little or no income taxes.Such a change in the distribution of taxes, creating a large percentage of earners and tax-filers with no income-tax liability, will then bring consequences similar to those in the United States today where large and persistent deficits are common and decisions on the cost of government are deferred to the future. The only way to encourage Canadians to consider the economic costs and benefits of government programs is to ensure that most Canadians, not just a few, are responsible for paying the price of government.The key to avoiding such a situation is restraint in applying what should be narrowly targeted tax programs like the WITB so Canada can enjoy the benefits of these programs without incurring the political cost the United States has incurred by aggressively expanding them.
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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 | 0.003 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.017 |
| Science and technology studies | 0.020 | 0.007 |
| Scholarly communication | 0.013 | 0.006 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.003 | 0.007 |
| 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".