Discriminatory Immigration Bans Elicit Anti-Americanism in Targeted Communities: Evidence from Nigerian Expatriates
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
Abstract Do discriminatory US immigration policies affect foreign public opinion about Americans? When examining negative reactions to US actions perceived as bullying on the world stage, existing research has focused either on US policies that involve direct foreign military intervention or seek to influence foreign countries’ domestic economic policy or policies advocating minority representation. We argue that US immigration policies – especially when they are perceived as discriminatory – can similarly generate anti-American sentiment. We use a conjoint experiment embedded in a unique survey of Nigerian expatriates in Ghana. Comparing respondents before and after President Trump surpisingly announced a ban on Nigerian immigration to the United States, we find a large drop (13 percentage points) in Nigerian’s favorability towards Americans.
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.001 | 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