Experiences of discrimination and discomfort: A comparison of metropolitan and non‐metropolitan locations
Bibliographic record
Abstract
This article compares feelings of discomfort and experiences of discrimination attributed to racial and ethnic difference among visible minorities and two white groups: “Europeans” and “white charter” individuals. In conducting the analysis, attention is given to the role of location by examining how responses vary in three types of locations in Canada: large and diverse metropolitan areas, smaller “second‐tier” cities, and towns and rural areas. Using the Ethnic Diversity Survey (EDS) as the principal data source, the results of descriptive and explanatory multivariate analyses are presented. Logistic regression analyses confirm that race frequently is interpreted as underlying experiences of discomfort and discrimination in Canada, with visible minorities much more likely to report racial and ethnic discomfort and discrimination than the two white groups. While location is not strongly related to racial and ethnic discrimination, it has a significant impact on reports of discomfort. Residents of Montreal, Toronto, and Vancouver are more likely to report racial and ethnic discomfort than those living in non‐metropolitan areas. As others have reported in Australia and Great Britain, living in diverse social environments where negotiation of difference is an everyday necessity heightens discomfort. The findings highlight geographical variations in the lived experience of multiculturalism that warrant further investigation.
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How this classification was reachedexpand
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.006 |
| Scholarly communication | 0.000 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".