The T/Daos shall meet: The failure and success of English transliterations of Mandarin Chinese
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
When a Canadian exchange student returns home from a semester abroad in the capital city of China, she might tell her friends that she had Peking duck every day, but she would never, as a 21 st -century liberal arts student, say that she stayed in Peking for a semester. Rather, she would say Beijing, as would most English speakers in the present day. But such discrepancies between English transliterations of Chinese words are far from uncommon. Is it the Nanking Massacre or the Nanjing Massacre? Who is the author of Tao Te Ching : Lao-Tzu or Laozi? What, then, is the Daodejing ? This paper will focus on the English representation of Mandarin Chinese phonology, particularly the consonant sounds. The inconsistency of English transliteration of Mandarin is caused by historical exchanges and encounters between the British and the Chinese and a lack of a monolithic standardization of Mandarin. Paradoxically, while these transliterations attempt to unify and standardize themselves and the representation of Mandarin sounds, they simultaneously represent the concept of a diverse Mandarin.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it