On James E. Bosson’s Translation of A Treasury of Aphoristic Jewels: The Subhsitarstnanidhi of Sa Skya Pandita in Tibetan and Mongolian
Bibliographic record
Abstract
From the perspective of history, literature and translatology, this article discusses in depth the translation of Bosson and holds that: (1) his selection of source language text (SLT) should be timely—his adaptation to the social and historical context of the United States and the theme of the era; (2) his interpretation of SLT is much accurate since Bosson has devoted all his life to Tibetan and Mongolian studies; however, there still exists some under-translation—the translation carries less information than the original, Bosson fails to reproduce the deep meanings of SLT related to Tibetan culture; (3) his literal translation or foreignization, making the version featured by a purely linguistic translation method, in order to help the intended readers to insight into the laws how to render the Mongolian, or Tibetan into English; and (4) his expression in the version tends to be colloquial, and be rich in foreignized expressions. All these reflect the subjectivity from Bosson, as a linguistic translator, non-literary translator. Furthermore, Bosson’s subjectivity is not only an adaptation to the social and historical context, the theme of the era, but also a limited transcendence of these constraints.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".