Acquisition of the Tap-Trill Contrast by L1 Mandarin–L2 English–L3 Spanish Speakers
Bibliographic record
Abstract
The goals of this study were to investigate the developmental patterns of acquisition of the Spanish tap and trill by L1 Mandarin–L2 English–L3 Spanish speakers, and to examine the extent to which the L1 and the L2 influenced the L3 productions. Twenty L1 Mandarin–L2 English–L3 Spanish speakers performed a reading task that elicited production of rhotics from the speakers’ L3 Spanish, L2 English, and L1 Mandarin, as well as the L2 English flap. The least proficient speakers produced a single substitution initially, generally [l]. The same non-target segment was produced for both rhotics, mirroring the results of previous studies investigating L1 English–L2 Spanish speakers, indicating that this may be a universal simplification strategy. In contrast to previous work on L1 English speakers, the L1 Mandarin–L2 English–L3 Spanish speakers who had acquired the tap did not tend to use it as the primary substitute for the trill. Overall, the L1 was a stronger source of cross-linguistic influence. Nonetheless, evidence of positive and negative L2 transfer was also found. The L2 flap allophone facilitated acquisition of the L3 tap, whereas non-target productions of the L2 /ɹ/ were also observed, revealing that both previously learned languages were possible sources of cross-linguistic influence.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".