Bibliographic record
Abstract
This paper presents an attempt at conducting an analysis of the notion “optionality” based on the works of experts in the given sphere. There is a certain lack of consistency in the matter of understanding and interpretation of the given phenomenon in the linguistic literature.Some scientists mean by optionality an opportunity to substitute one synonymic word by the other without significant changes in the plane of content; others recognize ellipsis in it, while the third party-an optional combinability.The issue of faculty has obtained the widest discussion in sinology. According to one of the theories, optionality can be studied against redundancy and economy of language means. In this case the phenomenon of optionality in the Chinese language can manifest itself on the level of phonemes, morphemes and lexemes. Functioning of grammatical markers expressing aspect, tense, number, etc. can serve as an example, as it possesses the property of optionality.The majority of scholars agree that optionality is an objective property of language system and is closely connected with the process of the language ongoing development.
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 | 0.005 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.005 | 0.024 |
| Scholarly communication | 0.005 | 0.013 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".