Bibliographic record
Abstract
Foreign language education may serve many goals, but national storytelling would not be an obvious one. Due to the position of English as an international language, it has become an increasingly important tool for intercultural communication and international public relations for countries whose official language is not English. In this study, we will look into the case of China, where English has been seen as the most important medium of China’s national storytelling. Chinese youths are encouraged to learn English well and to equip themselves with the competence to tell China’s stories well in English. As a key theoretical underpinning in this study, national stories are taken as national identities to live by. To better understand this relationship, we have invited 100 undergraduate English Majors in a provincial Chinese university to each tell a China story in English. By subjecting the 100 China stories told by 100 Chinese youths in English to a rigorous thematic analysis, we hope to determine in this study what Chinese national identity is constructed through this national storytelling exercise. More importantly, by examining the Chinese case of English as a medium of national storytelling, this study aims to shed light on the specific purpose of English as a global medium for communicating a country’s national narratives and national discourses.
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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 | 0.004 | 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 | 0.008 | 0.005 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".