The categorization of the relative complementizer phrase in third-language English: A feature re-assembly account
Bibliographic record
Abstract
Research questions: The study considers (1) the nature of multilingual transfer in the pre-intermediate stage of third-language (L3) English and (2) the upper limit of L3 ultimate attainment with respect to the acquisition of definite and indefinite restrictive relative clauses. Methodology: The methodology used was four-point scale acceptability judgment tasks testing (un)-grammatical relative sentences. Data and analysis: The accuracy scores of two control groups of French ( n = 15) and English ( n = 12) natives and two groups of pre-intermediate ( n = 11) and advanced ( n = 15) adult learners of L3 English are submitted to parametric statistical analysis. Findings: The results of the pre-intermediate L3 learners indicate that the relative complementizer phrase structure is available as a block from the earlier stages, while the feature matrix of the complementizer is a hybrid of first-language (L1) Arabic and second-language (L2) French features [EPP, ±definite, –wh]. The L3 interlanguage at this stage presents simultaneous L1 non-facilitative and L2 facilitative transfer effects. The performance of the advanced L3 learners shows that they can successfully re-assemble the features of the complementizer matrix substituting the target [–wh] for the native [±definite]. Originality: This article uses a novel language triplet L1 Arabic–L2 French–L3 English to investigate the L3 acquisition of restrictive relatives in a formal foreign language context. The focus is on the interplay between the (in)-definiteness of the head noun and the nature of the complementizer. Significance/implications: The study extends the viability of Lardiere’s feature re-assembly account of L2 acquisition to L3 acquisition. The (in)-definiteness of the head noun of the relative clause needs adequate attention in language teaching, like the much-highlighted aspects of resumption.
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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 | 0.002 | 0.004 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".