The Populist Appeal: Personality and Antiestablishment Communication
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
With the election of Donald Trump and landmark wins for populists across Europe, one of today’s most pressing questions is: Why do people support populists? We theorize that citizens who score low on the personality trait agreeableness—those who are more distrusting, cynical, and tough-minded—are more susceptible to antiestablishment messages expressed by populists. Using 13 population-based cross-sectional samples collected in eight countries and three continents, we first show that individuals who score low on agreeableness are more likely to support populists. Moreover, with a conjoint experiment, we demonstrate that it is their antiestablishment message that makes populists attractive to people who score low on agreeableness. As such, this article outlines a broader theoretical framework that links personality to political persuasion. In a time when politicians tailor their messages to the psychological makeup of their voters, it is crucial to understand the interplay between political communication and personality.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| 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