Some Observations on Net Fiscal Transfers to Recent Immigrants Resulting From Income Taxes and Government Transfer Programs
Bibliographic record
Abstract
This paper utilizes the comprehensive data on income\ntaxes paid by immigrants and others and the government transfer payments received by immigrants and others provided by the 2006 Census from income tax statistics.\nThe Census data was recently made available to researchers in the 2006 Census PublicUse Microdata File (PUMF), which contains 844,476 records, presenting census data on\nindividuals representing 2.7 per cent of the Canadian population. \n\nThe analysis revealed that recent immigrants on average only paid about half as much income tax as native Canadians\n($4,172.69 per capita compared to $8,130.82). It also showed that the most recent cohort of immigrants from 2000 to 2004 paid only 40 per cent as much income tax as native\nCanadians.\n\nIn the Other Government Transfer Income category, which is a catch-all for “all transfer payments, excluding those covered as a separate income source (child benefits, old age\nsecurity pensions and guaranteed income supplements, Canada or Quebec Pension Plan benefits and employment insurance benefits) received from federal, provincial, territorial\nor municipal programs,immigrants received per capita amounts in 2005 that are $13.05 less than nonimmigrants\nso there is no prima facie evidence of disproportionate reliance on social assistance from the Census. The one area where recent immigrants got a disproportionate share of government transfers is child benefits. This reflects their larger number of dependent children, which could be a result of their lower average age or greater proclivity to have children. On the other hand, recent immigrants received a lower per capita amount of employment insurance benefits. This could reflect their tendency to locate in areas with stricter eligibility requirements for EI such as the TorontoMetropolitan Region in 2005. Taking into account Other Government Transfer Income,Child Benefits and Employment Insurance, recent immigrants received $346.15 more per capita from Government Transfers than non-immigrants. In total, this would amount to $534 million, an amount that is small in relation to the fiscal transfer resulting from lower per capita income taxes paid.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".