Spatial and Socioeconomic Analysis of Latin Americans and Whites in the Toronto CMA
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.
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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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it