Counter-Examples in Linguistics (Science): The Case of Circassian as a Split Anaphor Language
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Linguists often resist data that undermines the dominant paradigm to which they adhere. This paper examines split anaphors in Circassian, a language of the Caucasus, as a case study of such rejection. A typology of counterexamples is devised and contrastively applied to physics and to linguistics, with etTortsmade to cite examples from each field. The split anaphor case is presented as an error in prediction and hence as a refutation of the Government and Binding paradigm. Its treatment is contrasted with that of the orbit of Mercury, a comparable error in prediction of Newto-nian mechanics. A symmetry-breaking approach is taken to the problem of split anaphor (in which reflexivesare ergativewhile reciprocals are anti-ergative).A new expla-nation for ergativity is offered. This explanation predicts that only ergative languages with a particular rule coupling will exhibit split ergativity. 1.
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.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 it