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
Why are American cities, suburbs, and towns so distinct? Compared to European cities, those in the United States are characterized by lower densities and greater distances; neat, geometric layouts; an abundance of green space; a greater level of social segregation reflected in space; and—perhaps most noticeably—a greater share of individual, single-family detached housing. In Zoned in the USA , Sonia A. Hirt argues that zoning laws are among the important but understudied reasons for the cross-continental differences.Hirt shows that rather than being imported from Europe, U.S. municipal zoning law was in fact an institution that quickly developed its own, distinctly American profile. A distinct spatial culture of individualism—founded on an ideal of separate, single-family residences apart from the dirt and turmoil of industrial and agricultural production—has driven much of municipal regulation, defined land-use, and, ultimately, shaped American life. Hirt explores municipal zoning from a comparative and international perspective, drawing on archival resources and contemporary land-use laws from England, Germany, France, Australia, Russia, Canada, and Japan to challenge assumptions about American cities and the laws that guide them.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 it