Functional categories in second and third language acquisition : a cross-linguistic study of the acquisition of English and French by Chinese and Vietnamese speakers
Bibliographic record
Abstract
This thesis investigates non-native language acquisition of the verbal and nominal functional domains in Second language (L2) English and second/third language (L2/L3) French by Chinese and Vietnamese speakers. Six experimental studies are reported. Two current competing theories in the field of theoretical second language acquisition (L2A), namely, the Failed Features Hypothesis (FFH) and the Full Transfer Full Access (FTFA) model are compared and their applicability to third language acquisition (L3A) evaluated in the light of our data. A version of the Minimalist Program is assumed in this work. Predictions based on FFH and FTFA are as follows: As far as L2A is concerned, both FFH and FTFA predict full transfer of L1 in the L2 initial state. With respect to L3A, FFH predicts the initial state to be L1 while FTFA predicts either L1 or L2. The two models diverge regarding their predictions on the L2/L3 transitional and steady states. In particular, FFH hypothesizes permanent "failure" and persistent L1 influence in L2/L3 interlanguage while FTFA hypothesizes full access and acquirability of target structures. Three L2/L3 experimental studies on the verbal functional domain (i.e. tense and agreement) and another three on the nominal functional domain (i.e. the Determiner Phrase) were conducted. Subjects include Chinese monolingual learners of English, Vietnamese monolingual learners of French as well as Chinese-English bilingual learners of French. A variety of tasks were used to test the predictions made by the two models. Results demonstrate partial transfer of L1 in the L2 initial state and of L2 in the L3 initial state, and point towards full access in the L2/L3 steady states. These findings do not seem to be consistent with FFH. It appears that FTFA is a more viable theory for non-native language acquisition. We also contend that L3A is not simply another case of L2A.
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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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".