Beyond the Lockdown Binary: Family Caregiver Needs for Creative Solutions During a Global Pandemic
Bibliographic record
Abstract
Abstract As COVID-19 lockdowns began in Canada last spring, family caregivers (FCGs) of people living with dementia (PLWD) found themselves facing a catch-22: they and their family members were often most at risk of severe outcomes should they contract the virus, yet the public health measures put in place also detrimentally affected their ability to continue providing care. To understand the nuances of caregiver experiences during the pandemic, we conducted 9 focus groups with 19 FCGs of PLWD in the Calgary region in summer 2020. Caregivers reported negative outcomes resulting from decreased services for both themselves and the PLWD, including increased isolation, poor mental health, and accelerated dementia progression. Caregivers also emphasized the importance thinking beyond the binary of either locking down or opening up; rather, we must find creative solutions to safely continue providing supports to caregivers. This presentation explores FCG suggestions for balancing COVID-19 risk against caregiver needs.
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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 | 0.015 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.014 | 0.010 |
| Scholarly communication | 0.008 | 0.007 |
| Open science | 0.002 | 0.010 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.005 | 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".