Urban population density distribution: a contribution from the Vancouver case
Bibliographic record
Abstract
Colin Clark's model of the negative exponential population density decay function is applied to the Vancouver case. Though the model is claimed to hold true for all places at all times, it does not offer sufficient explanations why the process is occurring, nor does it pay due regards to the topographical effects. The application of the model to the east and south sections of Vancouver may throw some light to the rationale of the city growth process. We are able to compare the density gradient of the east and south due to the different timing of transportation improvement and physical morphology. By examining two sections of the same city we can isolate the effect of transportation on the density of development, since both sections are subject to the same growth pressures. The density profiles of the whole city, and the eastern and southern sections of it (in the shape of ring, single airline, sector and band) are prepared; and for each plotting of population density, two parallel regression runs are made with regard to both radial distance and travel time. The model is tested at four points in time; and its goodness of fit is measured by the coefficients of determination. The conclusions reached are as follows: 1. The quality of the model in replicating the Vancouver experience is similar to that found for a wide range of cities. 2. The east and the south are marked by the differential rates of density decline, which are mainly due to the date at which the development takes place. 3. The distance parameter measured in travel time from the CBD does not give a significantly better fit to the model than radial distance from the CBD. 4. The coefficients of determination of the model decline over time, suggesting variable pattern of population density within the city over time. 5. The imputed central density does not show a consistent decline over time. 6. The steepness of density decline decreases in the course of time.
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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 | 0.001 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".