How have Asians experienced discrimination differently during COVID-19? The role of nativity
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
In this article, we consider differences in how native-born Asians and foreign-born Asians may have experienced rising anti-Asian attacks during the COVID-19 pandemic. We analyze Canadian data from a national survey (two waves conducted in April and December 2020) that includes a subsample of 464 Asians (native-born=178; foreign-born=286). Results from negative binomial regressions suggest that perception of anti-Asian racism is highly conditioned by nativity. Specifically, native-born Asians are significantly more likely than foreign-born Asians to report having encountered instances of acute discrimination during the pandemic. To explain the perceived discrimination gap, we test whether a stronger sense of cultural belonging and ethnic pride among native-born Asians contributes to their greater sensitivity to discrimination and thereby higher perceptions of discrimination. We measure sense of cultural belonging and ethnic pride using in-group trust (ethnic trust in Asian people). Although we do find native-born Asians show greater in-group trust, it does not seem to explain away the higher levels of discrimination perceived by native-born Asians.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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