Beyond the subject DP versus the subject pronoun divide in agreement switches
Bibliographic record
Abstract
Previous code-switching literature argues that no switch takes place between a pronoun and a verb, while Determiner Phrases (DPs) do code-switch. This paper uses code-switching acceptability judgment data elicited from three groups of English–Spanish bilinguals (2L1 children, L2 English children and L2 English adults) to test: (i) van Gelderen & MacSwan’s (2008) PF disjunction theorem intended to account for the DP/pronoun divide; and (ii) an agreement version of the analogical criterion (Liceras et al. 2008) which is based on Pesetsky & Torrego’s (2001) double-feature valuation mechanism intended to account for the different status of third person versus first and second person pronominal subjects. We show that the PF disjunction theorem is clearly rooted in the mind of the bilingual and that the Spanish dominant bilinguals can ‘relax’ its requirements to value person agreement features as predicted by the double-feature valuation mechanism.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".