Spatial and Socioeconomic Analysis of Latin Americans and Whites in the Toronto CMA
Bibliographic record
Abstract
This study had three objectives: (1) to determine whether the degree of residential segregation between Latin Americans and whites in the Toronto CMA was higher than the residential segregation between whites and other visible minority groups; (2) to determine the spatial distribution of Latin Americans and whites by census tracts; and (3) to determine the differences in the socioeconomic quality of the neighborhoods where the two groups reside. Data from Statistics Canada’ s 1996 Proe le Series were used. An index of dissimilarity was used to measure segregation and a composite socioeconomic index was constructed to assess inequality in the socioeconomic characteristics of neighborhoods where the two groups reside. The results revealed that Latin Americans and whites are not highly segregated in terms of residence. Yet, socioeconomic inequality between whites and Latin American neighborhoods is very evident. Whites are disproportionately occupying the highest quality neighborhoods while the Latin Americans are disproportionately residing in poorer quality neighborhoods. The differences may be due to several factors including the recent immigration status of Latin Americans and discrimination.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".