Planning for Healthy Communities in Nova Scotia: The current state of practice.
Bibliographic record
Abstract
There is a growing recognition of the importance of the built environment in mediating people’s health related decisions, such as whether to walk rather than drive, or what types of food to purchase. The built environment has been identified as a significant determinant of health by the World Health Organization and many other organizations across the globe. This has spurred research on how and to what extent community design impacts health. Most research in Canada has been focused on major urban centres. Research in rural contexts on the connection between planning and health is limited. Despite much research on land-use and design to support healthy communities, how planners interpret the application of this research within the social, political, and jurisdictional confines of their planning practice is largely unexamined. Through an online survey and 10 semi-structured interviews with planners in Nova Scotia, the question of whether and how rural planners should address health issues is explored. The intention of this research is to better understand the connection rural planners see between their planning practice and health issues in their communities. This research found that planners indicated that health is important to address in planning practice, which confirms recent national level research. However, each respondent’s interpretation of health and how it related to planning practice was slightly different. Working with public health workers and agencies was supported as a way to improve community health, but most participants saw themselves as consultants to public health staff concerning projects and initiatives to support healthy communities rather than as collaborators. Provincial government “silos” were cited as the biggest barrier to implementation of planning practices to address health issues like physical inactivity. Results confirm what has been identified in the literature as barriers to rural planners addressing community health issues.
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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 | 0.005 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.005 | 0.004 |
| Scholarly communication | 0.007 | 0.001 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".