Preregistered Replication of “Feeling Superior Is a Bipartisan Issue: Extremity (Not Direction) of Political Views Predicts Perceived Belief Superiority”
Bibliographic record
Abstract
There is currently a debate in political psychology about whether dogmatism and belief superiority are symmetric or asymmetric across the ideological spectrum. Toner, Leary, Asher, and Jongman-Sereno (2013) found that dogmatism was higher among conservatives than liberals, but both conservatives and liberals with extreme attitudes reported higher perceived superiority of beliefs. In the current study, we conducted a preregistered direct and conceptual replication of this previous research using a large nationally representative sample. Consistent with Toner et al.'s findings, our results showed that conservatives had higher dogmatism scores than liberals, whereas both conservative and liberal extreme attitudes were associated with higher belief superiority compared with more moderate attitudes. As in their study, we also found that whether conservative or liberal attitudes were associated with higher belief superiority was topic dependent. Contrasting Toner et al.'s findings, our results also showed that ideologically extreme individuals had higher dogmatism. We discuss implications of these results for theoretical debates in political psychology.
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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 | 0.009 | 0.029 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.018 | 0.003 |
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".