The Competing Influence of Policy Content and Political Cues: Cross-Border Evidence from the United States and Canada
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
When individuals evaluate policies, they consider both the policy’s content and its endorsers. In this study, we investigate the conditions under which these sometimes competing factors guide preferences. In an effort to combat the spread of COVID-19, American President Trump and Canadian Prime Minister Trudeau bilaterally agreed to close their shared border to refugee claimants and asylum seekers. These ideologically opposed leaders endorsing a common policy allows us to test the influence of a well-known foreign neighbor on domestic policy evaluations. With a large cross-national survey experiment, we first find that Canadians and Americans follow ideological positions in evaluating the policy, with right-leaning respondents offering the most support. With an experiment, we reveal how both populations shift their views when told about their neighboring leader’s endorsement. Our findings highlight ideologically motivated reasoning across an international border, with broad implications for understanding how individuals weigh a policy’s content against its political cues.
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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 | 0.003 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.009 |
| 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