The Structure of Income Residential Segregation in Canadian Metropolitan Areas
Bibliographic record
Abstract
Structure of Income Residential Segregation in Canadian Metropolitan Areas. Factorial ecology studies have long identified socio-economic status or income to be one of the most important dimensions of variation or residential segregation in the social ecology of the city. Recent studies have argued that residential segregation is a multidimensional construct, to be conceptualised as: i) geographical unevenness; ii) the probability of exposure of minorities to the majority; iii) the degree of spatial concentration or relative density of minority groups; iv) the degree of inner city centralisation of a minority; and v) the degree of clustering or spatial contiguity amongst minority neighbourhoods. Within the context of the urban system important insights can be gained into the dynamics of social and spatial polarisation by understanding the dimensions of segregation. This study investigates the dimensionality of income residential segregation in the Canadian metropolitan system, and finds that the structure is three-dimensional, representing: Unevenness and Isolation; Concentration and Clustering; and Centralised Density. This means that claims for a five-dimensional structure of segregation may not be universally valid, but may differ for different types of social segregation. The paper identifies how a multiple dimensional approach to income segregation provides insights into the system-wide spatial patterns of segregation for income minorities. It also shows that if a single index of segregation is required, without concern for pattern effects, little is to be gained by this more complex analysis over the traditional use of the Index of Dissimilarity. [much less than] The Structure of Income Residential Segregation in Canadian Metropolitan Areas [much greater than] [La structure de la segregation residentielle par revenue clans les regions metropolitaires du Canada]. Les etudes dans le domaine de l'ecologie factorielle ont depuis longtemps identifie le statut socio-economique ou le revenu comme une des dimensions les plus importantes clans la variation ou clans la segregation residentielle dans l'ecologie sociale de la ville. Des etudes recentes ont raisonne que la segregation residentielle est une construction multi-dimensionnelle comportant: i) une repartition geographique inegale; ii) la probabilite de contact des minorites a la majorite; iii) le degre de concentration spatiale ou la densite relative des groupes minoritaires; iv) le degre de centralisation au centre-ville d'une minorite; et v) le degre de groupement ou de contiguite parmi les quartiers contenant des minorites. Dans le contexte du systeme urbain, une comprehens ion importante de la dynamique de la polarisation sociale et spatiale est fournie par une analyse des dimensions de la segregation. Cette etude explore les dimensions multiples de la segregation residentielle par revenu dans le systeme metropolitain canadien, et conclut que la structure comporte trois dimensions : Une repartition inegale et l'isolement; la concentration et le regroupement; et la densite centralisee. Ceci suggere que d'autres interpretations suggerant une structure de la segregation en cinq dimensions ne sont pas necessairement valides, mais que cette structure pourrait varier selon les differents types de segregation sociale. Dans cet article, on montre comment une approche multi-dimensionnelle la segregation par revenu fournit des perspectives sur les repartitions geographiques de segregation sociale pour des minorites definies par revenu a l'echelle du systeme entier. On demontre aussi que si une seule indice est recherchee, sans se preoccuper pour des effets de repartition geographique, l'approche plus complexe utilisee ici contribue peu de valeur ajoutee en comparaison a l' utilisation traditionnelle de l'Indice de dissemblance. ********** Although interest in the measurement and description of social areas within cities has recently waned, during the 1970s and 1980s factorial ecology -- an approach that can be seen as a continuation of a long intellectual tradition that bridged the sociological and geographical study of the social character of cities-- contributed to the understanding of urban social structure and the spatial patterns of these social structures (Davies 1984). …
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.005 | 0.008 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".