The acquisition of a novel phonetic category in a foreign language setting: Input versus phonological awareness
Bibliographic record
Abstract
Input-related factors are fundamental for the acquisition of new second language (L2) phones (e.g., Flege et al., 1995). Nonetheless, evidence from instructional settings suggests that, in foreign language contexts, input alone may not be sufficient for the formation of new phonetic categories. In the present study, we investigated to what extent the acquisition of a novel L2 phone (/ð/) is associated with input-related variables and phonological awareness. First language (L1) Brazilian Portuguese speakers of English answered a language background, a phonological self-awareness questionnaire, and completed a paragraph reading task and a phonological awareness test. The recordings were submitted to acoustic analysis and accuracy assessment by Brazilian teachers of English. Linear mixed-effects models revealed that perceived accuracy was predicted by input quality and phonological self-awareness, suggesting that greater interaction with L1 speakers of the target language and heightened phonological self-awareness play an important role in the acquisition of the tested L2 phone.
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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 | 0.007 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".