Innovative care: Using ‘A day in the life’ as a tool to explore opportunities for a tech-enabled home for older Canadians
Bibliographic record
Abstract
Caregivers play a crucial role in providing physical and emotional support to family members or clients with various health conditions. As the number of older adult population and the potential need for caregiver support increases, innovative solutions are essential in supplementing care provided by caregivers. Many studies have been conducted to date to understand the extent to which technologies can be used to address health conditions and disabilities. Assured Living is a wellness monitoring solution by Best Buy Canada designed to provide caregivers insights on family member’s daily activities and provide alerts. To bring Assured Living into the Canadian market, an A Day in the Life was created as a tool to aid in identifying the needs of the caregivers to explore opportunities in the Canadian market. The knowledge for the A Day in the Life was gathered in multiple ways: 1) meetings with health organizations, 2) meetings with organizations serving caregivers and seniors, 3) conversations with family caregivers, 4) observations during walk-throughs with internal and external stakeholders of the Assured Living lab located in Best Buy Canada headquarters. Five themes gathered from the tool include: 1) Safety 2) Activities of daily living 3) Virtual care 4) Enjoyment of life and 5) Overarching concerns about support and communication. A Day in the Life supported in determining general concerns for caregivers, identifying areas of opportunity for the business, and making collaboration with stakeholders effective.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.012 | 0.005 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".