Bibliographic record
Abstract
During World War I, Britain and France imported workers from their colonies to labor behind the front lines. The single largest group of support labor came not from imperial colonies, however, but from China. Xu Guoqi tells the remarkable story of the 140,000 Chinese men recruited for the Allied war effort. These laborers, mostly illiterate peasants from north China, came voluntarily and worked in Europe longer than any other group. Xu explores China's reasons for sending its citizens to help the British and French (and, later, the Americans), the backgrounds of the workers, their difficult transit to Europe - across the Pacific, through Canada, and over the Atlantic - and their experiences with the Allied armies. It was the first encounter with Westerners for most of these Chinese peasants, and Xu also considers the story from their perspective: how they understood this distant war, the racism and suspicion they faced, and their attempts to hold on to their culture so far from home. In recovering this fascinating lost story, Xu highlights the Chinese contribution to World War I and illuminates the essential role these unsung laborers played in modern China's search for a new national identity on the global stage.
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.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.024 | 0.014 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".