CHARITABLE GIVING AND THE SUPERDEDUCTION: AN INVESTIGATION OF TAXPAYER PHILANTHROPIC BEHAVIOR FOLLOWING THE MOVE FROM A TAX DEDUCTION TO A TAX CREDIT SYSTEM
Bibliographic record
Abstract
Governments often encourage charitable giving through the tax system, by a deduction or tax credit. In 1988, Canada moved from a deduction system to a tax credit system. The tax credit for donations above $250 was calculated at the highest tax rate, even if the taxpayer was at the lowest tax rate. This gives what can be called a “superdeduction.” At the same time, the top rate of tax was reduced. Thus, the cost of giving was reduced for the lower taxpayers and increased for the higher-income taxpayers.The article reports whether taxpayer behavior changed from 1986 (pre reform) to 1988 and 1992 (post reform). The analysis also investigates the influence of inflation on the charitable donations. The percentage of taxpayers giving over $250 was analysed for both all the taxpayers and those consistently in the low and high tax brackets. The lower-income taxpayers were found to reduce their giving, contrary to expectations. The middle-income taxpayers, in general, increased their giving, which was expected and so took advantage of the superdeduction. The results of the moderate high-income taxpayers were mixed. Taxpayers who had very high incomes decreased their giving, as was expected.
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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 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".