First- and final-semester non-native students in an English-medium university: Judgments of their speech by university peers
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
By the end of their studies, non-native speakers of English studying at English-medium universities have had several years of exposure to English in that setting. Do non-native students, particularly those enrolled in non-languagerelated programs, show different levels of second language (L2) speaking ability in their final semester of studies than non-native students in their first semester, as judged by other students in the university community? In this exploratory cross-sectional study, two matched groups of L2 English university students in their first or final semester of study in non-language-related programs (N = 20) were recorded in mock job interviews. The students were rated by two groups of raters for accentedness, comprehensibility, fluency, and communicative effectiveness. Both rater groups were university students; one group was from diverse academic programs, while the other group was studying human resource management (HRM). Although the first- and final-semester L2 English students differed in how long they had studied in English, no significant difference in ratings between first- and final-semester students was found. However, the two rater groups differed in how they rated accentedness and comprehensibility, suggesting that the nature of listeners' previous academic experience (e.g., with HRM) influences their judgments. The use of holistic rating scales to evaluate L2 speech is discussed, as well as the relationship between the nature of language exposure and the performance of the student and rater groups.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it