Places of paid work and unpaid work: Caregiving and work‐from‐home during COVID‐19
Bibliographic record
Abstract
Eldercare and places of eldercare have been radicalized with the advent of COVID-19. Growing concerns about the safety of long-term care homes, coupled with the continuation of stay-at-home orders, mean that carers are reconstructing new meanings and places of care provision. Increasingly for many Canadians, the home is rapidly becoming the nexus of one's domestic, work, and caregiving world. By interviewing working carers (n = 5) living throughout Canada, this study investigates the changing meanings of home as a place for care during the COVID-19 pandemic. Drawing upon lived experiences of informal carers engaged in the workforce, we observe a blurring of spatial and temporal boundaries between places of work and places of care. Specifically, we note that the integration of carescapes and workscapes into a single domain presents both benefits and tensions to carers, such as increased schedule flexibility and disruptions at work, respectively. Parallel to this, we also explore how previous places of safety and respite, such as independent senior residences and long-term care homes, are perceived as sites of danger and anxiety due to the vulnerability of seniors to COVID-19. This dynamic is likely to continue well into the future, as long-term care homes fall out of favour and carers adopt a more integrated approach to caregiving within their daily lives.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.013 | 0.007 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.001 | 0.002 |
| 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".