Bibliographic record
Abstract
Historians generally agree that American suburbanization began in the first quarter of the nineteenth century, brought on by a combination of technological innovation (particularly in transportation), economic restructuring, and changing tastes of the urban middle classes. Essential to this process was the rise of a suburban real estate industry, which converted agricultural land into a consumer commodity. Using a microhistorical study of a single farm in the Boston suburb of Brookline, Massachusetts, the origins of the process of suburban land development are examined from 1770 to 1850. Land records, local history, and genealogical information were used to reconstruct the process by which farm land became the site of suburban neighborhoods. Before 1840, when nearly all land transactions were between individuals who knew each other personally, there was no infrastructure of real estate professionals and developers to facilitate suburban growth. During the 1840s, sales between strangers, facilitated by agents or auctioneers, quickly became the norm, and residential subdivisions aimed at varying income levels appeared, accompanied by developers and builders. Land went from being the essential component of family farming to a general commodity freely bought and sold, part of the broader evolution of the American economy into one dominated by market-based industrial and financial capitalism.
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.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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 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".