Digital and analogue spaces of care: How older adults are redefining care practices in the COVID-19 pandemic
Bibliographic record
Abstract
COVID-19 changed the way we care. Scholars have long argued that care often requires proximity, especially when it comes to care for, with, and by older adults. With lockdowns and the imposition of widespread public health guidelines aimed at curbing the spread of COVID-19, such as physically distancing and sheltering-in-place, in-person care practices became increasingly difficult. Yet, unlike disasters catalyzed by hurricanes or other natural hazards, physical and communications infrastructures remained largely intact during the pandemic. This situation opened the possibility for shifting care into digital spaces. In this paper, we study how older adults (ages 65 and up) in Canada and the USA navigated this abrupt turn towards digital spaces for care. Our findings are drawn from our larger mixed methods study investigating the everyday COVID-19 pandemic experiences of older adults, children, and teens, examining vulnerability, mobilities, and capacities. Not only are older adults frequently characterized as the recipients of care, but they are also typically (and erroneously) homogenized and stereotyped as vulnerable and tech-unsavvy. Exploring the ways in which older adults have provided, sought, received, avoided, and been denied care during the pandemic thus reveals the complex negotiations, contestations, and emancipatory possibilities of digital spaces of care. Our attention to the accessibility needs of diverse older adults serves as a vehicle for exploring issues of intersectionality in shaping digital care. We describe a range of digital care practices, ranging from telemedicine appointments and app-based communication to web-based volunteering and online social gatherings. We explore digital communication and connection between generations; the potential for such communication during the COVID-19 pandemic is unprecedented, in part due to the massive uptake of digital communication options such as online video conferencing programs. We discuss the mismatch between the possibilities made available through digital architectures and care practices, relations, needs, and desires of older adults. Drawing on feminist theorizations of care, we situate older adults as both givers and receivers of digital care and unpack the intertwining of their agency and vulnerability. Their innovations, spurred in part by diverse experiences with the aging process, the pandemic, loneliness, joy, and frustrations with care in the digital sphere, suggest radical practices and spaces for inclusive care during and after the pandemic. What is radical about such care is that it is based on everyday, even mundane, elements that often go unremarked, rather than any flashy (monetized) innovations developed by technology companies.
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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 | 0.004 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.011 | 0.014 |
| Scholarly communication | 0.009 | 0.008 |
| Open science | 0.001 | 0.012 |
| Research integrity | 0.002 | 0.003 |
| 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".