“Had they been children, we’d probably be tearing our shirts off!”: Canadian long-term care centres as an arena for necropolitics during the COVID-19 crisis
Bibliographic record
Abstract
The COVID-19 pandemic did not create but rather exposed and exacerbated long-standing vulnerabilities, marginalities, and inequalities deeply embedded in our societies. Moving beyond strictly medical and epidemiological explanations, this article offers a novel perspective on the disproportionate impacts of COVID-19 on dependent elderly people living in Residential and Long-Term Care Centres (CHSLDs) in the Province of Quebec, Canada. To achieve this, we draw on the concept of necropolitics, which refers to the mechanisms through which socio-political power is exercised to control life, death, and the conditions of existence. It reflects the State’s power to determine who is allowed to live and who is left to die. Through this lens, we argue that the high rates of infection and mortality in CHSLDs were not merely attributable to age or comorbidities but were instead the inevitable outcomes of numerous austerity and privatisation reforms that reflect systemic discrimination against the elderly. These reforms chronically underfunded long-term care, commodified essential services, deteriorated working conditions for healthcare professionals and support staff, reduced the quality and quantity of care, and weakened care facility infrastructures. By implicitly determining which lives were to be protected and prioritised, these reform policies had already sealed the fate of dependent elderly individuals long before the pandemic. Using necropolitics as an analytical framework, this article elucidates the structural causes (“the causes of the causes”) of these inequalities, marginalities, and vulnerabilities. It calls for a transformative approach to long-term care policies that can address these systemic issues and prevent such tragedies in the future.
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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 | 0.036 | 0.016 |
| Scholarly communication | 0.009 | 0.003 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.003 | 0.004 |
| 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".