Building and Sustaining Aging in Place Through the Naturally Occurring Retirement Community (NORC) Ambassadors Program
Bibliographic record
Abstract
Older adults overwhelmingly want to continue to age in place but would benefit from a community of support to do so. The Naturally Occurring Retirement Community (NORC) Ambassadors program - an initiative from University Health Network (UHN) OpenLab - uses a participatory approach to create sustainable, resident-led, aging-in-place groups in NORC buildings. NORC, which stands for Naturally Occurring Retirement Community, is a geographic designation used to describe an area, such as a building or a neighbourhood that has become home to a large number of older adults. Having a high concentration of older adults, NORCs are ideal settings for mobilizing communities and developing supportive networks. This article describes the creation and evaluation of the NORC Ambassadors program, which led to its inclusion as a foundational element of the model being implemented through the newly founded NORC Innovation Centre at the UHN.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".