INTERINSTITUTIONAL RELOCATIONS: DEVELOPING GUIDELINES AND MOBILIZING KNOWLEDGE
Bibliographic record
Abstract
Increasingly, long-term care (LTC) facilities need redevelopment due to the complexity of resident care needs and to meet higher standards of accommodation. Redevelopments require relocation of staff and residents en masse. While significant literature exists on the negative health and well-being outcomes of older adults’ relocation from their private homes into care homes, less research has focused on the relocation of staff and residents together from one LTC facility to another following construction of a replacement facility. This presentation will report on an integrated knowledge translation (KT) project that developed guidelines through active collaboration with a LTC provider, a synthesis review of the literature, deliberative dialogues with stakeholders across Canada, and comprehensive dissemination. Engaging knowledge users throughout the project contributed to the relevance and impact of the guidelines. Using this research as a case example, the challenges and strategies for bridging research and practice through integrated KT will be discussed.
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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 | 0.129 | 0.179 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.007 | 0.005 |
| Science and technology studies | 0.010 | 0.015 |
| Scholarly communication | 0.014 | 0.015 |
| Open science | 0.007 | 0.024 |
| Research integrity | 0.007 | 0.009 |
| Insufficient payload (model declined to judge) | 0.003 | 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".