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Record W2116978338 · doi:10.7202/022925ar

Changing Patterns of Residential Centrality : Population and Household Shift in Large Canadian CMAs, 1971-1996.

2005· article· en· W2116978338 on OpenAlexaffvenueabout
Trudi E. Bunting, Pierre Filion, Heath Priston

Bibliographic record

VenueCahiers de géographie du Québec · 2005
Typearticle
Languageen
FieldSocial Sciences
TopicMigration, Aging, and Tourism Studies
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsCentralityMetropolitan areaPopulationGeographyPeriod (music)DemographyPopulation densityEconomic geographyStatisticsSociologyMathematics

Abstract

fetched live from OpenAlex

The research focuses on Canadian CMAs with populations of 500 000 or greater over the period 1971-1996. It uses population density gradients and enumeration of population and household shift to assess changing patterns of residential centrality over the twenty-five year period. Results indicate that all of the CMAs examined have experienced continued outward dispersion, some more so than others. When population change in core and inner-city zones is examined in conjunction with reduced density gradients, only one Canadian metropolitan area, Vancouver, shows indisputable signs of strong recentralization. Three other CMAs, Toronto, Victoria and Calgary, also experience some re-population of their central parts, while Montréal and Québec City are shown to maintain what we call "residual" centrality. However, when recentralization is gauged using household enumeration instead of population counts, all of the places studied show evidence of new housing production in the central city. The answer to the central question regarding residential centrality is thus a mixed one, yes and no. Overall, we conclude that there is a direct link between evolutionary patterns within the national urban System and changes observed in residential centrality. Whatever the measure used, highest rates of recentralization accompany strong metropolitan-wide growth over the 25-year period.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.188
Threshold uncertainty score0.457

Codex and Gemma teacher scores by category

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

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 head0.009
GPT teacher head0.229
Teacher spread0.220 · 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 teacher head, 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

Citations14
Published2005
Admission routes3
Has abstractyes

Explore more

Same venueCahiers de géographie du QuébecSame topicMigration, Aging, and Tourism StudiesFrench-language works237,207