Social network development of the Stay on Your Feet (SOYF) implementation in the Greater Sudbury Region: A case study
Bibliographic record
Abstract
The aging of the Canadian population is a serious concern. There are calls for innovation, \nintegration, and collaboration among health and social systems to address older adult care needs. \nThe rate of falls among older adults is high and will increase as the older adult population \nexpands and progresses through the later life course. Stay on Your Feet (SOYF), an evidencebased falls prevention initiative, has been implemented in northeastern Ontario. Social Network \nAnalysis (SNA) and semi-structured interviews were used to examine the implementation of \nSOYF in the Greater Sudbury region. The network was consisted predominantly of informal \ncollaborations among health-related organizations, had low density and high centrality. \nFurthering community recognition and engagement of older adults were indicated as necessary to \nachieve sustainability of SOYF. The SOYF implementation network could use more \ncollaboration among health and social organizations.
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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 | 0.001 | 0.000 |
| 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 | 0.001 | 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 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".