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Record W7070700569

A Quantitative Analysis of the Urban Morphology of Southwestern Ontario Census Metropolitan Areas

2010· article· en· W7070700569 on OpenAlexaboutno aff

Bibliographic record

VenueScholarship@Western (Western University) · 2010
Typearticle
Languageen
FieldEngineering
TopicUrban Design and Spatial Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsMetropolitan areaCensusNeighbourhood (mathematics)Urban morphologyUrban planningSpatial ecologyQuantitative analysis (chemistry)Statistical analysis
DOInot available

Abstract

fetched live from OpenAlex

Patterns of urban development in North America have changed drastically over time: from dense urban cores to sprawling subdivisions. This study investigates changes in residential forms of Southwestern Ontario cities by characterizing numerous individual features which make up the built environment, and then evaluating spatial patterns and statistical relationships. Using high-quality data regarding the social and physical elements of Ontario cities within a geographic information system (GIS), this research provides improved methods to quantitatively characterize urban development forms at the micro level. Results show that the majority of morphological variables have systematic spatial patterns and are highly correlated. Most variables tend to either increase or decrease from the city centre outward, or have their extreme values in the oldest residential neighbourhoods. Results show that social and historical variables of a neighbourhood are highly correlated with morphology. This research has implications for planners, land developers, and other agents of urban change.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.179
Threshold uncertainty score0.361

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0040.007
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.057
GPT teacher head0.269
Teacher spread0.213 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2010
Admission routes1
Has abstractyes

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