Bibliographic record
Abstract
This study assesses the claim that English late learners of Spanish do not perceive stress like native Spanish speakers, and that a short targeted stress perception training intervention during a study abroad Spanish language course has clear positive effects on stress perception. Fifteen English speakers were exposed to 90 hours of Spanish lessons during a three–week study abroad experience in Mar del Plata, Argentina. The trained group (N = 8) received 10 minutes of perceptual training on vowel and stress contrasts with nonce words three days a week, while the L1 English control group (N = 7) received communicative training focused on consonants, and the native Spanish control group (N = 7) received no training. Participants’ perception was assessed at pretest and posttest, both consisting of identification tasks with nonce words. Results indicated that all English speakers experienced difficulties in perceiving Spanish stress when compared to native Spanish speakers in the pretest. At posttest, however, the English trained group performed comparably to the native Spanish group and differed significantly from the control group, indicating an effect of training on the perception of L2 stress. The results show that English speakers evidenced perceptual difficulties when learning Spanish stress, which could be overcome with a small dose of targeted training with nonce words. Even though L2 immersion in a study abroad context was beneficial for the acquisition of Spanish stress, only students receiving stress training performed like native speakers.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.008 | 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".