Bibliographic record
Abstract
Much of contemporary American political rhetoric is characterized by liberals and conservatives advancing arguments for the morality of their respective political positions. However, research suggests such moral rhetoric is largely ineffective for persuading those who do not already hold one's position because advocates advancing these arguments fail to account for the divergent moral commitments that undergird America's political divisions. Building on this, we hypothesize that (a) political advocates spontaneously make arguments grounded in their own moral values, not the values of those targeted for persuasion, and (b) political arguments reframed to appeal to the moral values of those holding the opposing political position are typically more effective. We find support for these claims across six studies involving diverse political issues, including same-sex marriage, universal health care, military spending, and adopting English as the nation's official langauge. Mediation and moderation analyses further indicated that reframed moral appeals were persuasive because they increased the apparent agreement between the political position and the targeted individuals' moral values.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.004 |
| Scholarly communication | 0.009 | 0.011 |
| Open science | 0.001 | 0.013 |
| Research integrity | 0.004 | 0.008 |
| Insufficient payload (model declined to judge) | 0.149 | 0.064 |
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 source (direct Gemma or distilled Codex), 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".