“Be a Machine”: International Graduate Students’ Narratives around High-Stakes English Tests
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
The number of internationally mobile students pursuing higher education increases each year, with 8 million students expected to study abroad globally by 2025 (Farrugia, 2014). Many English-dominant universities require international applicants to provide standardized test scores as evidence of English proficiency. Accordingly, millions of students write tests such as the International English Language Testing System (IELTS) and the Test of English as a Foreign Language (TOEFL) each year. Much research has investigated these tests’ technical properties; however, less has explored the lived experiences around these tests. The current paper responds to calls for research investigating test-takers’ perspectives and contributes to research about the social and personal impact of such tests. It centers on the life stories of four Canadian-based international graduate students who took the IELTS or TOEFL. Through narrative portraiture we explore how language tests may enable and constrain these students’ life choices. The paper is guided by this research question: What do successful test-takers’ narratives about learning English and navigating high-stakes English tests reveal about the relationship between student agency and durable structures?
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 | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 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