Parallel scaling of elite wealth in ancient Roman and modern cities with implications for understanding urban inequality
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
Abstract Rapid urbanization and rising inequality are pressing global concerns, yet inequality is an ancient trait of city life that may be intrinsically connected to urbanism itself. Here we investigate how elite wealth scales with urban population size across culture and time by analyzing ancient Roman and modern cities. Using Bayesian models to address archeological uncertainties, we uncovered a consistent correlation between population size and physical expressions of elite wealth in urban spaces. These patterns suggest the presence of an ancient, enduring mechanism underlying urban inequality. Supported by an agent-based network simulation and informed by the settlement scaling theory, we propose that the observed patterns arise from common preferential attachment in social networks—a simple, yet powerful, driver of unequal access to interaction potential. Our findings open up new directions in urban scaling research and underscore the importance of understanding long-term urban dynamics to chart a course toward a fairer urban future.
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 | 0.000 | 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