Understanding Partisan Cue Receptivity: Tests of Predictions from the Bounded Rationality and Expressive Utility Perspectives
Why this work is in the frame
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Bibliographic record
Abstract
Why do citizens rely on partisan cues when forming political judgments? We assess the relative importance of two motives for partisan cue-following using a series of survey experiments. We find no support for the bounded rationality hypothesis that cue receptivity is highest among citizens with low cognitive resources. Meanwhile, we find mixed support for the expressive utility hypothesis that cue receptivity is highest among people with both a strong partisan social identification and high cognitive resources. The strength of this latter evidence varies across studies, cognitive resource measures, and cue condition comparisons. The results suggest that partisan cue receptivity more often involves an effort to harness cognitive resources for the goal of identity expression than an effort to compensate for low cognitive resources.
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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 | 0.001 | 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 | 0.000 | 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) | 0.000 | 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