Bibliographic record
Abstract
As one of the most active scholars in the field of Chinese run-on sentence (CRS for short), Wang and Zhao (2016) keenly realize that CRS displays distinctive traits of spatiality, namely, chunkiness, discreteness and reversibility, among which, the last trait and the iconicity of sequence/order (e.g. Haiman, 1984, 1985) seem to depict a diametrically opposite picture. In the present article, there would be an attempt to undertake an investigation of Wang, Zhao et al.’s ‘reversibility’ to see whether or not CRS is an exception to the iconicity of sequence/order. The main arguments are as follows. First, ‘reversibility’ is borne out to be local by some linguistic facts, especially in: (i) duyuju within CRS; and (ii) shuncheng CRS. Second, although the ‘reversibility’ sometimes exhibits a tendency to change the positions of clauses/syntagms in CRS, there is a clear correlation between the clause order of CRS and iconicity. The sequence/order principle in practice emerges as a cognitive mechanism emitting some effects in the clause order of CRS. Third, the Reversibility Condition is required to come into being so as to arrive at a detailed specification of the applicable scope of the ‘reversibility’. And finally, it is more preferable to ameliorate the spatiality of CRS as two traits, that is, chunkiness and discreteness.
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 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 | 0.002 | 0.098 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".