Stroad Efficiency and Walkability: An Intersection of Economy, Community Wellbeing, and Public Safety
Bibliographic record
Abstract
Between 2010 and 2019, there has been a reported estimate of 1,160 pedestrian accidents in the Atlanta-Sandy Spring-Roswell Area. The rate of pedestrian-related accidents increases yearly. This research focuses on and analyzes design factors in urban design and how it impacts pedestrians' walkability, safety, and health in Sandy Springs, Georgia. The term “stroad” has been used to describe a combination of streets and roads found throughout many locations throughout the United States and Canada, including Sandy Springs, Georgia. These “stroads” have been considered dangerous and unsustainable for pedestrian and cyclist usage. Many cities in Georgia have made walkability and cycling a low priority as a means of transportation in favor of vehicle access. This has impacted many pedestrians from the Sandy Springs area who come from low-income backgrounds and/or don’t have access to vehicle transportation. In cities like New York, Seattle, and San Francisco, there have been efforts to improve and expand upon sustainable pedestrian and cyclist infrastructure. Data on the statistics and rates of pedestrian accidents/deaths and demographics most impacted was gathered through relevant articles and news reports. Data on urban design factors and their impact on walkability and health was gathered through relevant articles and books. After research was conducted, various methods of urban design, including road diets, easy access to public transportation, elimination of the left turn lane, and expansion of sidewalks, were common solutions in places that suffered the “stroad” problem. This research hopes to analyze these improvements as potential solutions for Sandy Spring’s urban design and raise attention to the factors of urban design, the demographics most impacted, and its connection with pedestrian safety to a wider audience.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.001 | 0.001 |
| 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".