Derivation and Validation of Metropolitan Sprawl Indices
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
A metropolitan area is a region that consists of a densely populated urban core and its less-populated surrounding territories that are economically and socially linked to it. Parenthetically, a total of seven metropolitan areas and divisions were ultimately dropped from our sample due to the lack of Local Employment Dynamics (LED) data, a key data source for measuring sprawl. Low residential density is on everyone&s;s list of sprawl indicators. Segregated land uses are also on most lists of sprawl development patterns. Conversely, mixed and integrated land uses sit atop lists of pedestrian-friendly, transit-oriented, and smart growth patterns. Commercial strip development is on most lists of sprawl development patterns. Centering is the compactness dimension with the most significant improvement compared to earlier indices. Street connectivity is related to block size since smaller blocks translate into shorter and more direct routes. The metropolitan area now includes Vancouver, WA, and its surroundings, in addition to the Portland PMSA.
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.
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 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 it