ISQUA18-2303Every Voice Counts: A Community Engagement Approach to Understanding Life in Long Term Care from the Perspective of Every Resident Living in Publicly Funded Seniors Care Homes in British Columbia Cda.
Bibliographic record
Abstract
Objectives: The British Columbia (CANADA) Office of the Seniors Advocate funded a province-wide survey using a volunteer management model to conduct structured interviews with over 22 K residents living in 296 care homes in the province. Learn how we: ... Methods: Over 850 volunteers were screened, recruited, trained and deployed to sit with residents, often for over an hour, to engage with them, learn their life story and give them the opportunity to provide feedback about life in residential care. Volunteers from across BC participated in 128 in person and online training sessions on how to conduct structured interviews to ensure interrater reliability in administering the interRAI Self-Reported Resident Quality of Life Survey and the VR-12. In addition training included topics such as, infection prevention, privacy, communicating with people with dementia, how to use the visual analogue boards developed for the project, the survey website to register for shifts, and how to record evaluative and narrative responses.
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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 | 0.019 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.015 | 0.006 |
| Scholarly communication | 0.008 | 0.003 |
| Open science | 0.003 | 0.011 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.020 | 0.002 |
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".