Understanding Chinese Multilingual Scholars' Experiences of Publishing Research in English
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
Despite sporadic reports on the publishing experiences in English of Chinese academics in Hong Kong and in mainland China (mainly doctoral students), little research has been conducted on a large scale to reveal how mainland Chinese academics perceive international publishing in English and what challenges they face. This study intends to fill this research gap. The findings we report come from a large-scale research project involving an online survey of 118 academics at eighteen universities in Shanghai, China. By analysing participant responses to the survey and interviews with eight academics, we show how the motivations of these academics contribute to their language choice for academic publishing. We discuss the implications of these findings for the wider academic community with regard to writing and publishing research articles in English as an international language.
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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 | 0.018 | 0.035 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.057 | 0.154 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.000 | 0.003 |
| 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