Bibliographic record
Abstract
Local planning for an aging population in Ontario is multi-sectorial, involving a variety of policy initiatives and a complex funding system. It is important to understand what planning bodies have jurisdiction over issues associated with aging in the community, the extent to which such issues are acknowledged and acted upon, and how these planning initiatives come together in a local context. This paper examines planning activity related to aging issues in two contrasting upper-tier municipalities, Simcoe County and Metropolitan Toronto (prior to amalgamation), as case studies. Planning documents from the upper-tier municipalities, their constituent lower-tier municipalities, and corresponding District Health Councils were reviewed. On the surface, the aging of the populations of these two municipalities appeared to be much the same as for the province as a whole. However, the context in which these populations were aging was very different, not just at the upper-tier level, but also between and within their lower-tier municipalities. The specific aging related issues identified by the local planning bodies and the approaches used to address them varied considerably, often at a very local, neighbourhood level. It was found that in the absence of other contextual information, the proportion of the elderly in the population per se can be a poor indicator of the specific planning issues which develop.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 | 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 | 0.001 | 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".