“A Crisis in the Urban Landscape,” “The Origins and Theory of Type,” and “Legitimacy and Control”
Bibliographic record
Abstract
Although typically associated with nineteenth-century industrialization, the seeds of sprawl in the United States were planted with the early institutionalization of strong individual property rights, the country’s frontier spirit, and the rise of profit-driven speculative development. With the building of streetcar lines, first and second ring suburbs were built around the historic centers of towns and cities, beginning their stretch into previously peripheral areas. The massive proliferation of sprawl, however, is largely associated with late industrialization, the widespread distribution of automobiles and freeways, the rise of zoning practices that emphasized low-density development, federal tax programs that provided economic incentives to both homebuyers and builders, and an ever-increasing volume and scale of production housing by corporate developers. Post-war production of tract housing exacerbated the speed and march of sprawl in historic developments such as Levittown, and continues across many parts of the world today. Although this reading focuses primarily on the United States, indicators of sprawl can be seen from Canada to Australia, South Africa to Southeast Asia.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.023 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".