Bibliographic record
Abstract
The articles and book reviews included in this issue of China Report resulted from symposiums held in New York and Kolkata in 2006–07.1 The theme of these symposiums was the Chinese Indian community in Kolkata and featured Rafeeq Ellias's moving documentary on the Chinese Indians called The Legend of Fat Mama. Two issues were evident to the participants and audiences of these symposiums. First, very few people knew about the history and experiences of the Chinese community in India. Second, although exchanges between Kolkata, which was named the capital of British India in 1772, and China seem to have started in the last quarter of the eighteenth century and flourished during nineteenth and early twentieth centuries, little attempt has been made to study these interactions. This issue is the first step in redressing some of these deficiencies. Only two aspects related to the ‘unexplored’ links between Kolkata and China are highlighted in this collection. The first three articles and the two book reviews focus on the Chinese Indian community in Kolkata. The fourth and fifth articles examine the travelogues of Bengalis who visited China during the first half of the twentieth century.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.010 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.007 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.029 | 0.004 |
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".