Political Tolerance, Racist Speech, and the Influence of Social Networks*
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
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.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.003 | 0.021 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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