COVID-19-related deaths in long-term care: The moral failure to care and prepare
Bibliographic record
Abstract
Coronavirus disease 2019 (COVID-19) has taken a particularly heavy toll on long-term care (LTC) home residents in Western countries.Almost 80% of Canada's 1 and 50% of Switzerland's 2 coronavirus-related deaths are linked to LTC facilities even under hermetically closed lockdown conditions.Half of the COVID-19-related deaths in Europe 3,4 and 35% of the US death toll 5 are happening in LTC facilities.Although demographical and epidemiological factors like old age and comorbidities have been proposed to explain the excess mortality of this especially vulnerable population, 6 it has become more and more evident that it is not only the vulnerability of individuals but also the place of care that is the major contributing factor capable of explaining this dramatic phenomenon.The failure to plan adequately in this sector, while acute and critical settings received most of the pandemic planning attention, is a reflection of the longstanding low visibility of these care environments.As the unsettling stories of neglect and undignified deaths in LTC facilities continue to unfold, the problem of how we treat older adults, people with disabilities, and those who care for them has been laid bare by the pandemic.The inability of LTC to cope with the devastating impact of COVID-19 within its institutions comes as no surprise.It is a result of the deep-rooted devaluation of care work that happens at the intersection of ageism, ableism, sexism, and racism and is further aggravated by a rude marketization of this healthcare sector.When human value is mainly tied to economic contribution, old and disabled bodies are perceived to have outlived their usefulness and, thus, are undervalued.Contributions that older and disabled adults have made throughout their lives and continue to make to their families, communities, and society and their past work are often unrecognized.Fragility and dependency are negatively perceived as a burden.Thus, provision of care for this group of individuals is not considered a priority, and they are often left in insecure and vulnerable positions.The perception of care work as trivial or of less importance has also contributed to the current crisis in LTC during the pandemic.Care work is not considered a fundamental component of growth and development under neoliberal capitalist ideologies ruling healthcare markets.The existing attitude toward care work is that this work is "low-skilled" by nature and, therefore, a type of work that anyone can do.Women, particularly women of color, have been disproportionately overrepresented in this sector.7 Care workers, the
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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 | 0.022 | 0.065 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.012 | 0.017 |
| Scholarly communication | 0.008 | 0.005 |
| Open science | 0.001 | 0.010 |
| Research integrity | 0.008 | 0.018 |
| Insufficient payload (model declined to judge) | 0.008 | 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".