DISCOVERING THE RELATIONSHIP BETWEEN CONTEXT AND ALLOPHONES IN A SECOND LANGUAGE
Bibliographic record
Abstract
The identification of stressed syllables by adult second-language (L2) Spanish learners was examined for evidence of influence of an allophonic alternation driven by word position and stress. The Spanish voiced stop-approximant alternation, whereby stops occur in stressed-syllable and word onsets, was utilized. If L2 learners track the distribution of this alternation, they should tend to link stops to stressed syllables in word-onset position and approximants to unstressed, word-medial position. Low- and high-intermediate-level first-language English learners of Spanish as well as native Spanish and monolingual English speakers listened to a series of nonce words and determined which of the two consonant-vowel (CV) syllables they perceived as stressed. In Experiment 1, onset allophone and vowel stress were crossed. In Experiment 2, the onset allophone alternated and a vowel unmarked for prominence was used. The results show that the monolingual English and low-intermediate groups were more likely to perceive syllables with stressed vowels as stressed, regardless of the allophone onset. In contrast, listeners with greater Spanish proficiency performed similarly to native Spanish speakers and were more likely to perceive stress on syllables with stop onsets, a pattern that follows the distributional information of Spanish. This finding suggests that learning the interplay between allophonic distributions and their conditioning factors is possible with experience and that knowledge of this relationship plays a role in the acquisition of L2 allophones.
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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 | 0.002 |
| 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) | 0.001 | 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".