Chinese Public Opinion about US–China Relations from Trump to Biden
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 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.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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