How Much Exposure to English Do International Graduate Students Really Get? Measuring Language Use in a Naturalistic Setting
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
Abstract: Many believe that the best way to learn a language is to study it in a country where that language is widely spoken. Underlying this belief is the assumption that study in a naturalistic setting will provide learners with ample opportunities for exposure to the target language and interaction with native-speakers of that language. This article reports the findings from a longitudinal study of the quantity and quality of exposure experienced by 17 Chinese graduate students at a Canadian university. Exposure was measured using a computerized log that participants completed once a month for one week, over a six-month period. Our findings show a general trend toward receptive rather than interactive use of English, and considerable variation among individuals in terms of the amount and type of language use. The discussion explores possible reasons for participants’ relatively low amount of oral interaction in English in this naturalistic setting.
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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