North American Attitudes toward Immigrants and Immigration in the Time of COVID-19: The Role of National Attachment and Threat
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
Using a cross-national representative survey conducted during the COVID-19 pandemic, we examine predictors of attitudes toward immigrants and immigration in Canada and the United States, including general and COVID-related nationalism, patriotism, and perceived personal and national economic and health threats. In both countries, nationalism, particularly COVID-related nationalism, predicted perceptions that immigration levels were too high and negative attitudes toward immigrants. Patriotism predicted negative immigration attitudes in the United States but not in Canada, where support for immigration and multiculturalism are part of national identity. Conversely, personal and national economic threat predicted negative immigration attitudes in Canada more than in the United States. In both countries, national health threat predicted more favorable views of immigration levels and attitudes toward immigrants, perhaps because many immigrants have provided frontline health care during the pandemic. Country-level cognition in context drives immigration attitudes and informs strategies for supporting more positive views of immigrants and immigration.
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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 | 0.002 | 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 | 0.000 | 0.018 |
| Scholarly communication | 0.000 | 0.000 |
| 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