Collaborative Partnership in Age-Friendly Cities: Two Case Studies From Quebec, Canada
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This article aims to explain the collaborative partnership conditions and factors that foster implementation effectiveness within the age-friendly cities (AFC) in Quebec (AFC-QC), Canada. Based on a community-building approach that emphasizes collaborative partnership, the AFC-QC implementation process is divided into three steps: (1) social diagnostic of older adults' needs; (2) an action plan based on a logic model; and (3) implementation through collaborations. AFC-QC promotes direct involvement of older adults and seniors' associations at each of the three steps of the implementation process, as well as other stakeholders in the community. Based on two contrasting case studies, this article illustrates the importance of collaborative partnership for the success of AFC implementation. Results show that stakeholders, agencies, and organizations are exposed to a new form of governance where coordination and collaborative partnership among members of the steering committee are essential. Furthermore, despite the importance of the senior associations' participation in the process, they encountered significant limits in the capacity of implementing age-friendly environments solely by themselves. In conclusion, we identify the main collaborative partnership conditions and factors in AFC-QC.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 it