Does empirical data from bilingual and native Spanish corpora meet linguistic theory? The role of discourse context in variation of subject expression
Bibliographic record
Abstract
Abstract The goal of this study is to shed light on how empirical data on the discourse constraints of null and overt third person subject pronouns in L1 and bilingual Spanish meet linguistic theory. A (semi)spontaneous production task was administered to 34 Moroccan Arabic (MA)/Spanish early sequential bilinguals and 30 L1 Spanish controls. All 3rd person subject positions were coded: (1) morphosyntactic form (null pronoun vs. overt pronoun); (2) discourse function ([-Topic Shift] vs. [+Topic Shift]); (3) sentence relation (intrasentential vs. intersentential); (4) clause order within intrasentential contexts (main-subordinate vs. subordinate-main); and (5) access to the antecedent (clear vs. ambiguous antecedent). The results reveal general patterns of use in both L1 and bilingual Spanish: null pronouns express topic maintenance both in inter- and intrasentential contexts (both clause orders) and overt pronouns, especially in intersentential contexts, are generally used for topic change. However, additional analyses provide evidence that null pronouns in L1, but not in bilingual Spanish, are often used in change of reference contexts where the antecedent is not ambiguous. This reveals patterns that have gone unreported by most previous descriptive and theoretical studies. Finally, a higher use of ambiguous null pronouns is attested among bilingual speakers, which suggests a lower control of the mechanisms by which reference is established in discourse and supports, to some extent, the predictions derived from the Interface Hypothesis.
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 | 0.005 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".