Korean honorific agreement as the marginal requirement for syntactic finiteness
Bibliographic record
Abstract
This is an accepted article with a DOI pre-assigned that is not yet published.This study argues that smaller-than-TP domains can be finite. This position contrasts with the conventional argument that finiteness of a clause is tied to T(ense), but it is in line with alternative proposals. The central claim is that subject-verb agreement is the minimum requirement for syntactic finiteness, defined as being syntactically opaque for cross-clausal operations. This argument is grounded on two key pillars: agreement features are in Hon(orific) P(hrase) in Korean, and HonP is located below TP. After introducing the two pillars, this study shows that HonP, rather than TP, is the smallest finite domain in Korean by analyzing two types of smaller-than-TP embeddings in Korean, HonP and vP. HonP acts as a finite domain in terms of blocking cross-clausal negative polarity item licensing and constituting a binding domain, but vP turns out to be transparent for these cross-clausal operations. I argue that vP is syntactically non-finite because it lacks agreement features. The observation in this study aligns with Turkish findings that a minimal projection with subject agreement is finite (Kornfilt 2007). In short, this paper provides additional evidence that subject agreement, regardless of T, is the determinant for the syntactic finiteness of a domain.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.006 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.011 | 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".