“Not Having the Energy to Even Live”: A Feminist Disability Perspective on Long COVID and Caregiving
Bibliographic record
Abstract
Long COVID is defined as the persistence of symptoms three or more months after infection with severe acute respiratory syndrome Coronavirus 2 (SARS‐CoV‐2/COVID‐19). A growing body of research documents the economic and social implications of this relatively new health condition, but, to date, only a handful of studies have considered the effects of Long COVID on caregiving (defined here as the unpaid care work provided in the home or community by family and friends). Through interviews with people with Long COVID (30) and caregivers (9) in British Columbia, Canada, our research aims to document how Long COVID is affecting caregiving in the home to inform supportive health and care policy responses. We apply a feminist critical disability studies perspective, which conceptualizes care as relational and disability as more than a medical diagnosis of impairments, but as the result of complex interactions between physical and mental differences and social understandings of them. Interviews were analyzed using reflexive thematic analysis to illustrate how the novel nature of Long COVID created unique effects on household caregiving. PwLC particularly note how the symptoms of brain fog and exhaustion negatively affected their ability to complete household care tasks, self‐care, and childcare, which in turn resulted in feelings of guilt. Lack of information about Long COVID created a heavy burden on PwLC and caregivers left to conduct research themselves, while medical gaslighting and lack of awareness about Long COVID generated demand for emotional labor and exacerbated burnout. Health and social policy innovation is urgently needed to respond to the needs of PwLC and their caregivers.
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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 | 0.010 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.024 | 0.067 |
| Scholarly communication | 0.010 | 0.011 |
| Open science | 0.002 | 0.010 |
| Research integrity | 0.004 | 0.007 |
| Insufficient payload (model declined to judge) | 0.003 | 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".