Are orthographic effects language specific? The influence of second language orthography on second language phoneme awareness
Bibliographic record
Abstract
ABSTRACT This research investigated first language (L1) and second language (L2) orthographic effects on L2 phoneme perception. Twenty-five native English learners of Russian (n = 13) and Mandarin (n = 12) participated in an auditory phoneme counting task, using stimuli organized along two parameters: consistency and homophony. The learners more successfully counted phonemes in L2 words with consistent letter–phoneme correspondences (e.g., всё /fsʲɔ/, three letters/three phonemes) than in words with inconsistent correspondences (e.g., звать /zvatʲ/, five letters/four phonemes), indicating that L2 phoneme awareness is influenced by L2 orthography and that orthographic effects are not limited to the L1. In addition, the lack of any L1 homophone effects suggests that L2 orthographic effects overrode any potential L1 orthographic interference for these intermediate-level learners, suggesting orthographic effects may be language specific.
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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 | 0.004 |
| 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 | 0.000 |
| 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".