Framing refugees: experimental evidence from the United States, Canada, and Australia
Bibliographic record
Abstract
The acceptance and resettlement of humanitarian migrants is a politically charged issue in many western democracies. Still, research focusing specifically on attitudes toward humanitarian migrants is limited. Political elites have sought to frame would-be refugees in different ways, with some emphasizing the need for a humanitarian response, and others portraying migrants as a threat to national security. Our research examines the extent to which the framing of would-be refugees shapes public attitudes toward refugee policy. We present results from an online survey-based experiment conducted in parallel in the United States (n = 3656), Canada (n = 2604), and Australia (n = 3608). Across these three country contexts, we show that framing refugees as potential terrorists – and therefore a threat – increases support for more restrictive refugee policies. By contrast, a sympathetic frame describing refugees as including families fleeing violence decreases support for more restrictive policies. At the same time, the efficacy of such frames varies across countries.
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How this classification was reachedexpand
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".