Patterning in Urban Population Densities: A Spatiotemporal Model Compared with Toronto 1971–2001
Why this work is in the frame
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Bibliographic record
Abstract
We build on the literature on population-density distributions, but translate the consensus cross-sectional progression into a three-dimensional and six-stage geographic information system (GIS) based ‘volcano’ model. Visual comparison and descriptive statistics show Toronto's recent density patterns to be very similar to those suggested by the model: the central density cluster has reversed its decline, while peripheral clusters have developed at increasing distances from downtown. Local autocorrelation (LISA) allowed areas of significant clustering and diversity to be mapped, and strong conformity was found between the model and Toronto's empirical patterns. Overall, density levels throughout the metropolitan area are homogenizing and randomizing, even while inner-city redensification and peripheral densification proceed.
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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