Homecare Safety Virtual Quality Improvement Collaboratives
Bibliographic record
Abstract
With Canada's aging population, innovations in technology and changes in patient preferences regarding where they receive care, there is a growing reliance on homecare services. Professionals in the homecare sector want to provide the best care possible for their clients, whereas homecare organizations look to foster a greater patient safety culture. The Canadian Patient Safety Institute and the Canadian Home Care Association conducted two learning collaboratives aimed at increasing quality improvement capability in homecare settings. Teams from across the country have increased their capacity and capability to engage patients and families, mitigate and prevent harm from homecare safety incidents such as falls and specifically address issues such as improving interprofessional collaboration, teamwork and communication.
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 | 0.034 | 0.046 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.007 | 0.002 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.003 | 0.014 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.043 | 0.005 |
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".