Walking in a winter wonderland? an assessment of winter maintenance and physical activity features in Smythe Park, Toronto
Bibliographic record
Abstract
Objective. To determine how the features, conditions, and maintenance of a low-income park affect the use of the park for physical activity during the winter months. Method. Direct observation of park use; assessment of park quality based on a developed assessment tool; and supplementary surveys with park users. Results. The park lacked winter park features (e.g. ice rink, tobogganing hill) and supporting amenities (e.g. washrooms, rental facilities). There was evidence of winter maintenance, however, it was inconsistent: most trails were cleared of snow on all visits, but large ice patches were present and had not been cleared. The park was used primarily for walking and dog walking, although respondents noted that the lack of maintenance in the park affected if they used it for physical activity. Conclusion. Winter maintenance of parks and the presence of winter features affect park use, with snow removal, ice removal, and the presence of bathrooms having a strong influence on physical activity levels in the winter months. Park planners should consider year-round maintenance and programming in order to promote engagement in physical activity during all seasons.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".