Who Doesn’t File a Tax Return? A Portrait of Non-Filers
Bibliographic record
Abstract
The Canada Revenue Agency administers dozens of cash transfer programs that require an annual personal income tax return to establish eligibility. Approximately 10–12 percent of Canadians, however, do not file a return; as a result, they will not receive the benefits for which they are otherwise eligible. In this article, we provide the first estimates of the number and characteristics of non-filers. We also estimate that the value of cash benefits lost to working-age non-filers was $1.7 billion in 2015. Previous literature suggests either a rational choice model of tax compliance (in which the costs of filing are weighed against its benefits) or a more complex behavioural model. Our study has important consequences for policy-making in terms of the administrative design and fiscal costs of public cash benefits attached to tax filing, the measurement of household incomes, and poverty rates.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 teacher head, 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".