Visualizing The Relationships Between Highways and Nearby Neighborhoods in Major Midwest Cities in the United States (2000 and 2010)
Bibliographic record
Abstract
The development of major roadways has been shown to negatively impact nearby neighborhoods, especially minority neighborhoods. Oftentimes these areas see an increase in poverty. This project aims to help visualize this issue, utilizing the United States Census Bureau for data, in multiple cities. U.S. Census Block data for 2000 and 2010 from three midwest cities, St. Louis, Chicago, and Detroit, will be utilized for this project. The buffer tool in ArcGIS Pro will be utilized to find blocks within close proximity (half a mile to one mile) to major roadways within these cities. On average, one mile reaches eight north-south city blocks and sixteen east-west city blocks. Blocks outside of these buffer zones are thought to be unlikely affected by the development of major roadways; however, it is not ruled out that some areas outside the buffer zone may show similar data to areas that are within the buffer. Multiple maps will be created to visualize the impact these major roadways may have on nearby neighborhoods. Areas within and outside the buffer zones will be compared by median household income. The impact of major roadways on nearby neighborhoods is important to study as the United States considers adding and updating its current infrastructure.
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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 | 0.001 | 0.000 |
| 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 | 0.000 | 0.000 |
| 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".