Bilinguals have a single computational system but two compartmentalized phonological grammars: Evidence from code-switching
Bibliographic record
Abstract
Classic linguistic models, such as Chomsky’s minimalist schematization of the human language faculty, were typically based on a ‘monolingual ideal’. More recently, models have been extended to bilingual cognition. For instance, MacSwan (2000) posited that bilingual individuals possess a single syntactic computational system and, crucially, two phonological systems. The current paper examines this possible architecture of the bilingual language faculty by utilizing code-switching data. Specifically, the natural speech of Maria, a habitual Spanish-English code-switcher from the Bangor Miami Corpus, was examined. For the interface of phonology, an analysis was completed on the frequency of syllabic structures used by Maria. Phonotactics were examined as the (unilingual) phonological systems of Spanish and English impose differential restrictions on the legality of complex onsets and codas. The results indicated that Maria’s language of use impacted the phonotactics of her speech, but that the context of use (unilingual or code-switched) did not. This suggests that Maria was alternating between encapsulated phonological systems when she was code-switching. For the interface of morphosyntax, syntactic dependencies within Maria’s code-switched speech and past literature were examined. The evidence illustrates that syntactic dependencies are indeed established within code-switched sentences, indicating that such constructions are derived from a single syntactic subset. Thus, the quantitative and qualitative results from this paper wholly support MacSwan’s original conjectures regarding the bilingual language faculty: bilingual cognition appears to be composed of a single computational system which builds multi-language syntactic structures, and more than one phonological system.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".