Caring Beyond National Borders: The YMCA and Chinese Laborers in World War I Europe
Bibliographic record
Abstract
It is well known that 175,000 Chinese laborers worked for Allied troops in Europe during World War I. This phenomenon has been recorded in major WWI histories and has become the topic of monographs in Chinese and Western languages. Chinese laborers solved the Allied problem of a serious manpower shortage and made contributions to military fieldwork, construction, and factory work. Comparatively speaking, few scholars have paid attention to the Christian work among the Chinese laborers, which gave them considerable comfort and assistance and which laid the foundation for other service to Chinese laborers in France. Though some people have a general understanding that the Young Men's Christian Association (including the British YMCA and the International Committee of the YMCA in North America) was the most active and energetic group in offering assistance to the Chinese laborers, little has been written that explains the YMCA operations among the laborers, preventing a fair and thorough evaluation of the YMCA's service to the Chinese laborers. This paper, based on material from the American YMCA Archives, the Canadian Church Archives, and some Chinese writings on this topic, attempts to investigate the origin, operation, and development of this YMCA international project and to assess its significance in church history and in modern China.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.013 | 0.007 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".