Landscape Design in Clear Zone: Effect of Landscape Variables on Pedestrian Health and Driver Safety
Bibliographic record
Abstract
The relationship between landscape installations and safety or pedestrian activity was evaluated in pilot studies. The sites selected for study were those adjacent to or within the areas often referred to as the “clear zone” of the transportation corridor, an area shared by pedestrians and driver perception. Case study research on the impact of environmental mitigation on driver safety is summarized to identify the landscape installations in the clear zone that appear to have an effect on safety. This is followed by case study research on the identification of variables that encourage walking for health purposes. Preliminary findings indicate that the improved definition of spatial edge resulting from typical curbside and median landscape treatment in the clear zone appears to solicit positive behavioral responses by either attracting pedestrian activity or improving driver safety. It is not possible to draw definitive conclusions from the results because of the small sample sizes in the pilot studies (a pedestrian survey included 52 responses), but indications are that the landscape in the clear zone may be having a positive impact on safety or pedestrian activity under certain circumstances. Both pilot studies were conducted separately in Canada and the United States.
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 | 0.018 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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".