Do Political Endorsements Affect Support for Conspiracy Theories?
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
Abstract Objectives This article examines how support for conspiracy theories is affected by political endorsement. By relying on the literature on partisan cues and the role of political identity (partisan or ideological) in shaping people's attitudes and behaviors, we argue that endorsement of conspiracy theories by political elites convergent (divergent) with one's political identity should increase (decrease) belief in said conspiracy theories. Methods We rely on data collected from over 10,000 respondents in Brazil to evaluate this hypothesis by embedding a wording experiment in questions tapping support for conspiracy theories. Results We find that partisans of the Workers' Party, a well‐established party with a strong base of supporters, are affected by political endorsements by showing greater (lower) support for conspiracy theories when endorsed by political elites convergent (divergent) with their political identity. Conclusion Our findings suggest that political endorsements of conspiracy theories exert similar effects as endorsements of other political issues or public policies.
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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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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