Rightsizing as Spatial Austerity in the American Rust Belt
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
‘Rightsizing’ is a planning paradigm currently being applied to shrinking cities in North America and Europe. The central idea is to avoid the trap of growth-oriented planning by restructuring the urban landscape around mixed-income, mixed-use clusters. By replacing the current sprawling inefficiency, proponents argue, environmental, equity, and infrastructure efficiency goals can be achieved. Some have worried however, that rightsizing is merely a newly packaged version of urban renewal. I argue that both framings are misplaced. Through a careful consideration of rightsizing plans in five US cities—Detroit, Flint, Rochester, Saginaw, and Youngstown—I argue that austerity urbanism is the more apt way to characterize actualized versions of the idea. Actualized rightsizing lacks the utopian modernism and Keynesian interventionism of urban renewal, and the progressive equity-oriented environmentalism idealized by its proponents.
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 | 0.000 | 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