A network analysis of the semantic evolution of ‘fruit’ and ‘stone’ in Tibeto-Burman languages
Bibliographic record
Abstract
Abstract The lexemes ‘fruit’ and ‘stone’ are known as the origins of the numeral classifiers for small round objects in many Tibeto-Burman languages. This paper employs a correlation-based network construction method to investigate the colexification networks of the two concepts in 58 + 68 Tibeto-Burman languages. A total of 104 concepts colexified with ‘fruit’ and 99 concepts colexified with ‘stone’ are organized into macro semantic classes. Semantic networks on the basis of the similarities in colexification patterns of concepts, as well as languages networks on the basis of the similarities in colexification patterns of languages, are constructed for ‘fruit’ and ‘stone’, respectively. The results indicate that classifiers for small round objects evolved from either ‘fruit’ or ‘stone’ are directly colexified with class terms in compound nouns denoting varieties of fruits/stones and the shape class of small round objects, indicating that they are diachronically related. However, ‘fruit’ and ‘stone’ differ significantly in their modes of deriving a classifier. Moreover, languages that have developed classifiers from ‘fruit’ are mostly from the Ngwi subgroup, whereas languages whose classifiers are colexified with ‘stone’ evolved independently.
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How this classification was reachedexpand
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".