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Record W2039043721 · doi:10.1353/dem.2000.0003

The spatial separation of the poor in Canadian cities

2000· article· en· W2039043721 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueDemography · 2000
Typearticle
Languageen
FieldSocial Sciences
TopicUrban, Neighborhood, and Segregation Studies
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsSeparation (statistics)CensusGeographyIndex of dissimilarityEthnic groupRedevelopmentPopulationSocioeconomicsDemographyEconomic growthSociologyPolitical scienceEconomics

Abstract

fetched live from OpenAlex

We used the 1991 Canadian census to examine the extent of spatial separation of the poor in Canadian cities. Although there were no extensive areas of blight, decay, or housing abandonment, we found high spatial separation of poor visible minorities in the selected cities. The index of dissimilarity indicates high segregation of poor blacks and moderate separation of poor Asians from the nonpoor population. We tested the effects of three major structural factors--racial and ethnic segregation, income segregation, and urban redevelopment--and found that racial and ethnic residential patterns are related strongly to the spatial separation of poor persons. The relationship between income segregation and spatial separation of the poor is not significant, however. We also found that the relationship between urban redevelopment and spatial separation of the poor pertains only to blacks. These findings suggest that blacks are vulnerable in the process of urban redevelopment.

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 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)0.000
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 score0.403
Threshold uncertainty score0.611

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.011
GPT teacher head0.269
Teacher spread0.258 · 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