The Bantu-Salish connection in determiner semantics
Bibliographic record
Abstract
This paper provides a semantic analysis of the D(eterminer)-system in Nata (Eastern Bantu), and compares it with the strikingly similar D-system of St’át’imcets (Salish). Our core proposal is that in both languages, the major distinction encoded by Ds correlates with the presence vs. absence of speaker commitment to the existence of a referent for the noun phrase.We show that neither Nata nor St’át’imcets Ds encode well-known distinctions like definiteness or specificity. Instead, they reflect the speaker’s (un)willingness to commit to the existence of a referent for the DP. Despite these parallels, the two D-systems are not identical. In St’át’imcets, the notion of existence is based on the speaker’s personal knowledge; in Nata, the existence Ds are also used for entities which are surmised to exist, or are future possibilities. We derive the difference between ‘knowledge of existence’ and ‘belief of existence’ from independent differences in the evidential systems of the two languages. This work contributes to the landscape of potential determiner meanings across languages.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.005 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".