Municipal winter trail design standards: includes a winter trail design standards GIS analysis of the city of Prince George city-wide trail system master plan
Bibliographic record
Abstract
Many cities in Canada have trail systems that provide recreational and commuting opportunities for their residents and visitors but have not developed or maintained their municipal trail system for winter snow-based trail activities. Trail standards exist for many types of trails, uses and environments but an integration of standards for winter recreational activities with that of municipal seasonal trail standards currently in use is necessary to encourage planning, design and maintenance of winter trails at the community level. Using a mixed-methods approach, research was conducted through a focused synthesis, questionnaires and a focus group towards developing an understanding of the existing level of winter trail planning knowledge and determining what the issues and desires of trail users are in regards to municipal winter trails. The results showed that very good standards exist for winter snow-based recreational and utilitarian purposes and that existing municipal multi-use trail standards only require maintenance to allow for snow-based trail activities. A GIS analysis of the city of Prince George was then conducted to illustrate the recommended winter trail standards from this research that can be used as part of the planning process to aid in the development of a winter trail system at the municipal level.
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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".