Rethinking the link between cognitive sophistication and politically motivated reasoning.
Bibliographic record
Abstract
Partisan disagreement over policy-relevant facts is a salient feature of contemporary American politics. Perhaps surprisingly, such disagreements are often the greatest among opposing partisans who are the most cognitively sophisticated. A prominent hypothesis for this phenomenon is that cognitive sophistication magnifies politically motivated reasoning-commonly defined as reasoning driven by the motivation to reach conclusions congenial to one's political group identity. Numerous experimental studies report evidence in favor of this hypothesis. However, in the designs of such studies, political group identity is often confounded with prior factual beliefs about the issue in question; and, crucially, reasoning can be affected by such beliefs in the absence of any political group motivation. This renders much existing evidence for the hypothesis ambiguous. To shed new light on this issue, we conducted three studies in which we statistically controlled for people's prior factual beliefs-attempting to isolate a direct effect of political group identity-when estimating the association between their cognitive sophistication, political group identity, and reasoning in the paradigmatic study design used in the literature. We observed a robust direct effect of political group identity on reasoning but found no evidence that cognitive sophistication magnified this effect. In contrast, we found fairly consistent evidence that cognitive sophistication magnified a direct effect of prior factual beliefs on reasoning. Our results suggest that there is currently a lack of clear empirical evidence that cognitive sophistication magnifies politically motivated reasoning as commonly understood and emphasize the conceptual and empirical challenges that confront tests of this hypothesis. (PsycInfo Database Record (c) 2021 APA, all rights reserved).
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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 | 0.010 | 0.060 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.005 |
| Scholarly communication | 0.004 | 0.006 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 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 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".