Chinese Public Opinion about US–China Relations from Trump to Biden
Bibliographic record
Abstract
Abstract Numerous public opinion surveys have found that Americans’ views of China have become extremely negative in recent years. Much less is understood about the trends in Chinese views of the USA and the countries’ bilateral relations. As leaders in both countries have come under public pressure about their policy stances toward the other side, it is critical to fill the gap. This study develops a theoretical argument about how a concern for political legitimacy may allow public opinion to influence foreign policy making in authoritarian countries, and it presents findings from a two-wave public opinion survey in China conducted before and after the 2020 US presidential election. The results show that Chinese evaluations of the bilateral relationship and of the USA slumped during the Trump era but rebounded somewhat after Biden took office. In addition, the majority of Chinese respondents believed their country to be the world’s largest and leading economy and favored China being the world’s leading power, either by itself or alongside the USA. Furthermore, younger and more educated respondents held more negative views, although these were mitigated by personal connections with and experiences in the USA. These findings have important policy implications.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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 source (direct Gemma or distilled Codex), 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".