Why is the rate of single‐parenthood lower in Canada than in the U.S.? A dynamic equilibrium analysis of welfare policies
Bibliographic record
Abstract
Abstract A critical question in the design of welfare policies is whether to target aid according to household composition, as was done in the U.S. under the Aid to Families with Dependent Children (AFDC) program, or to rely exclusively on means‐testing, as in Canada. Restricting aid to single mothers, for instance, has the potential to distort behaviour along three demographic margins: marriage, fertility, and divorce. We contrast the Canadian and the U.S. policies within an equilibrium model of household formation and human capital investment on children. Policy differences we consider are eligibility, dependence of transfers on the number of children, and generosity of transfers. Our simulations indicate that the policy differences can account for the higher rate of single‐parenthood in the U.S. They also show that Canadian welfare policy is more effective for fostering human capital accumulation among children from poor families. Interestingly, a majority of agents in our benchmark economy prefers a welfare system that targets single mothers (as the U.S. system does), yet (unlike the U.S. system) does not make transfers dependent on the number of children.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.000 |
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".