Bibliographic record
Abstract
Scottish medical missionary named James Maxwell (1836-1921) to preach the Word of God in the south of Taiwan.1 In 1871, the Canadian Presbyterian Mission began to work in the north of Taiwan2. The two Presbyterian Missions were unified into One Presbyterian Church of Taiwan in 19123. Therefore up until 1945, when Taiwan came out of the Japanese rule and returned to the Nationalist government, Taiwan could be seen as “a Presbyterian island, happily free from any sectarian rivalry”.4 It has to be pointed out that use of the Romanized script was basically promoted by the English Presbyterian Mission and took place mainly in southern Taiwan. Min is the abbreviation for the province of Fujian on the southeast coast of China and opposite to Taiwan. Southern Min refers to the dialect spoken in Fujian. Chinese immigrants from southern Fujian began to settle in the second half of the seventeenth century after Taiwan came under Manchu rule. Nowadays, Southern Min is called Taiwanese and is used by 73 % of the population in Taiwan.5 During the nineteenth century, Taiwan was known to the West as Formosa and Southern Min as Amoy, which is the traditional English transliteration of Xiamen in Southern Min.6 Reasons for the invention of the Romanization scheme
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.032 | 0.006 |
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".