Who Benefited from the Deduction-Inclusion Regime for Taxing Child Support?
Bibliographic record
Abstract
Prior to the 1996 federal budget, child support payments in Canada were deducted from the payer's income and included in the recipient's income. Because the payer's marginal tax rate was usually smaller than the recipient's, the government was providing a subsidy relative to a system without income inclusion and deduction. This paper presents a theoretical and empirical analysis of the incidence of this subsidy ? that is, it examines the distribution of this subsidy between payers and recipients of child support. It is shown that the critical variable in assessing the distribution of the benefit is the rate used to gross-up the payments to take tax into account. Based on a sample of court cases from 1986 to 1995, courts generally attempted to gross-up by the recipient's marginal tax rate. However, this rate was systematically underestimated, and the actual gross-up was usually less than the additional taxes owing by the recipient on the child support amount. Recipients of child support not only failed to receive a share of the tax savings, but usually had even less after-tax money than in a system without tax recognition for child support. In other words, recipients of child support, who are usually women, were not advantaged by the deduction-inclusion system and were in fact disadvantaged in most cases.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".