How neighborhoods came to matter more over time: A broad historical sketch
Bibliographic record
Abstract
The demise of neighbourhood-scale community has been lamented for decades. Tight-knit neighboring has indeed declined. However, its significance is colored by nostalgia. In cities and suburbs, the loosening of neighborhoods has encouraged residents and agents to create imaginary local communities, partly by fashioning local traditions. In changed form, community persists. Underlying it, for those able to choose, are individualistic calculations. With increasing homeownership more people have a financial stake in place, the investment aspects becoming prominent since the 1980s. Because most children attend local schools, the growing importance of education has made them a major factor in neighborhood choice, with financial implications. In counterpoint, lower-income households with little choice are constrained to neighborhoods where the disadvantages of crime, poor mobility, and indifferent schools are exacerbated by growing wealth inequality. The concept and reality of neighborhoods have never been more important, in urban studies and in urban life.
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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 | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".