Long-Term Effect of Donald Trump’s Usage of White Supremacist Rhetoric on Public Discourse
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 qualitative study performed a content analysis of the top 50 comments on a tweet about Donald Trump and his dinner with white supremacist Nick Fuentes. This study aimed to see if any long-lasting effects were caused by Trump's utilization of white supremacist dogmatic rhetoric. The comments were coded for relationships with each other and prevalent themes; five were apparent 1) Criticism of the media, 2) Mention of Trump's base, 3) Use of the term white supremacist, 4) Use of term antisemitism, 5) and Criticism of Trump or Republican Party. The most pervasive themes explored were the sentiment that Trump is associated with white supremacy, a notion that tarnished him and his base, according to the findings of this analysis.
 
 
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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 | 0.002 |
| Science and technology studies | 0.006 | 0.002 |
| 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