On the role of person in the mapping of syntactic features onto their interpretable counterparts
Bibliographic record
Abstract
Abstract Person features play a role in narrow-syntax processes. However, a person feature is often characterized as [±participant], a characterization that suggests pragmatic or semantic features. Relatedly, person has been the subject of an ongoing debate in the literature: one family of approaches argues that 3rd person is an elsewhere case, while another argues that it is a valued interpretable feature. This article provides a programatic argument that this disagreement has a principled basis. I argue that the representation of the features we identify as person changes between narrow syntax and the syntax-semantics interface. The tests and empirical descriptions are incongruent because they target different modules of the grammar and in turn different grammatical objects. The article thus contributes to our understanding of the division of labour among the modules, with a special focus on the autonomous status of narrow syntax.
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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 | 0.004 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.014 |
| Scholarly communication | 0.007 | 0.013 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".