Unequal Impact of COVID-19: Emergency Neoliberalism and Welfare Policy in Canada
Bibliographic record
Abstract
This paper examines Canada's liberal welfare state in relation to the COVID-19 pandemic. It argues that contrary to claims that the pandemic is affecting both rich and poor equally, its impact is both gendered, racialized and class-related. It thereby exacerbates existing social and health inequalities. Responsible for much of this is Canada's welfare state that reproduces established patterns of power that create systemic social and health inequalities. In addition, the responses of the Canadian liberal welfare state to the COVID-19 pandemic make explicit its underdeveloped nature and its difficulties in responding to social and health inequalities. This paper shows how the political foundation and organizational logic of the liberal welfare state promotes and reinforces existing inequalities. Similarly, its responses to the pandemic reflect crisis management that meets immediate urgencies but does little to provide long-term economic and social security to citizens.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.023 | 0.016 |
| Scholarly communication | 0.009 | 0.002 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.003 | 0.005 |
| 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".