アムド・チベット語におけるヤクの呼び分け --青海省ツェコ県の事例を中心に--
Bibliographic record
Abstract
アムド・チベット語におけるヤクの呼び分け -青海省ツェコ県の事例を中心に-海老原 志穂 How yaks are called in Amdo Tibetan? -Case study in Tsekog, Qinghai EBIHARA ShihoAbstract：Generally, individual ethnic groups have folk vocabularies that are deeply related to their lives.For example, Inuit is known to have hundreds of words for categorizing snow, while Japanese is known to have different words for the same fish at different stages of its growth.These lexical categorizations reflect the field in which each ethnic group takes a great interest.In the case of Tibet, Tibetan pastoralists have a systematic way of referring to livestock according to sex, age, role in herds, physical features (i.e., colors and patterns of fur, horns etc.) , and behavior.Though Tibetan has an extensive vocabulary for livestock, as far as I know, only a few detailed studies have yet been conducted on it.This paper applies linguistic analysis to data from Tsekog (rtse khog) to reveal the systematic terminology for cognizing yaks in Amdo Tibetan.Through this systematic terminology, we can begin to understand the cognition of Tibetan speakers, accumulated in a long time of the traditional pastoral life.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 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".