Political Tolerance, Racist Speech, and the Influence of Social Networks*
Bibliographic record
Abstract
Objective. This study examines the influence of ethnic and racial network diversity on young people's attitudes about speech rights in Canada by examining the impact of diversity on racist groups' speech compared to other objectionable speech. Methods. After reviewing prior work on diversity and political tolerance judgments, the study presents multinomial logistic regressions to assess the impact of network diversity on three types of political tolerance dispositions. The data are drawn from the Canadian Youth Study, a sample of 10th- and 11th-grade students in Quebec and Ontario (N=3,334). Results. The analysis suggests that exposure to racial and ethnic diversity in one's social networks decreases political tolerance of racist speech while simultaneously having a positive effect on political tolerance of other types of objectionable speech. Conclusions. The dual effects arguably represent an evolving norm of multicultural political tolerance, in which citizens endorse legal limits on racist speech. Future work should assess the extent to which target group distinctions in political tolerance judgments have evolved over time and across age cohorts.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".