The syntax of subject pronouns in heritage languages: Innovation and complexification
Bibliographic record
Abstract
This study aims to investigate syntactic change in situations of language contact. The languages included in the study are heritage Italo-Romance languages spoken in Argentina, Belgium, Brazil, Canada and Italy. All heritage speakers are either sequential or simultaneous bilinguals and the dominant language of the larger national society may affect their heritage language at different levels. Heritage speakers acquired their native heritage language naturalistically, but their competence differs from that of native monolinguals as a consequence of language contact. Since heritage speakers use their native language only in limited contexts, they are unbalanced bilinguals. Their weaker language is their native language, while the stronger language is the dominant language of the society. Focussing on discourse features involved in the distribution of different types of subject pronouns, the study shows how different subject pronouns interact with syntax and with information structure and what happens to discourse features when languages get in contact with others. The main hypothesis is that all types of subject pronouns (full, clitic and null) have the same internal structure; the differences in their interpretation depend on a discourse feature [R(eferential)]: when subject pronouns encode this feature, they are overt and referentially specific enough to obviate or switch reference; when subject pronouns lack this feature, they refer to the most salient discourse antecedent and are normally not phonologically realised. This proposal captures the distribution of null and overt subjects in heritage Italo-Romance varieties.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| 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 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".