Women, the intellectually humble, and liberals write more persuasive political arguments
Bibliographic record
Abstract
If sincere attempts at political persuasion are central to the functioning of democracy, then what attributes of individuals make them more persuasive toward fellow citizens? To examine this, we asked 594 Democrats and Republicans to write politically persuasive arguments on any topic of their choice and then gave those arguments to a US representative sample of 3,131 to rate the persuasiveness, totaling 54,686 judgments. We consistently found that arguments written by women, liberals, the intellectually humble, and those low on party identification were rated as more persuasive. These patterns were robust to controls for the demographics and partisanship of judges and persuaders, the topics written about, argument length, and the emotional sentiments of the arguments. Women's superior persuasiveness was partially, but not fully, explained by the fact that their arguments were longer, of a higher grade level, and expressed less dominance than men's. Intergroup dynamics also affected persuasiveness, as arguments written for in-party members were more persuasive than the ones written for out-party members. These findings suggest that an individual's personal and psychological characteristics durably provide them with a persuasive advantage when they engage in sincere attempts at changing the hearts and minds of fellow citizens.
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How this classification was reachedexpand
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 | 0.000 | 0.001 |
| 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 | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".