Linguistic Capital in the University and the Hegemony of English: Medieval Origins and Future Directions
Bibliographic record
Abstract
As the institution of university has evolved into a highly diverse educational community, the language of communication (or linguistic capital) in higher education plays a vital role. Therefore, English as a medium of instruction (EMI) became the dominant characteristic of academia in many parts of a (globalized) world. This growing influence of EMI has affected the scope of both higher education and academic research. Being a linguistic form of capital, the significance of English as a major linguistic resource can be analyzed historically since the institution of university was founded. In fact, EMI seems to have challenged the linguistic diversity and accessibility to higher education in the contemporary world. The case of Canadian higher education highlights new directions in the exploitation of the linguistic capital at university, and the emerging concept of a multilingual university could offer some unique opportunities for knowledge mobilization and access to higher education. Thus, the issue of linguistic capital at the current (globalized) university needs to be re-examined.
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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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.004 | 0.031 |
| Scholarly communication | 0.007 | 0.012 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".