Between Pride and Profit: A Case of Speaking the Jing Language
Bibliographic record
Abstract
This study investigates the role of speaking the Jing language in the contemporary context of China’s active engagement with Vietnam. Based on the fieldwork conducted in Dongxing Guangxi in January 2024, the study shows that the Jing language plays an important role in both maintaining the cultural heritage as pride and empowering the educational and employment trajectories as profit. More importantly, the capacity of speaking the Jing language can contribute to the social and medical communication between China and Vietnam. This can be manifested in terms of cultural communication with Vietnam and medical treatment for Vietnamese migrants. However, speaking the Jing language as pride is not always consistent with speaking the Jing language as profit. The internal differentiation within Vietnamese varieties may cause communication barriers for Jing speakers. The limited development of the Jing language also creates another layer of communication challenges for Jing people engaging in professional practices. How to mobilize the Jing language to facilitate the bilateral communication between China and Vietnam deserves our attention for future studies. The study has enriched the scope of the studies on language planning and policy in the borderlands. The study can shed lights on implementing language policy in China’s border provinces and provide practical implications to facilitate the political and economic communication between China and other neighbouring countries for border prosperity and border stability.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.029 | 0.021 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.004 | 0.006 |
| 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".