Income inequality and support for redistributive policies in Ontario: Who gets what, where, how, and who cares?
Bibliographic record
Abstract
Income inequality has risen steadily in Canada over the last three decades, and particularly in Ontario, where it has grown at a faster rate. While the public response to this growth remains unclear, policy responses to address the issue have largely failed. To date, the literature remains divided as to the nature of the relationship between income inequality and support for redistributive policies such as welfare spending. This article argues, however, that where a relationship exists between income inequality and public support for welfare spending, it is a negative one. This negative relationship is in part due to perceptions of deservingness and factors explained by institutionalism. Even if support for governmental action to address income inequality is considerable both in Ontario and in the rest of Canada, support for governmental welfare spending is low. These findings point toward a public that is largely unresponsive to the problem of growing income inequality in Ontario. The results have implications for the development of policies to address inequality effectively, both in Ontario and in the rest of Canada.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".