International Students as Lucrative Markets or Vulnerable Populations: A Critical Discourse Analysis of National and Institutional Events in Four Nations
Bibliographic record
Abstract
The migration of post-secondary students is an increasingly debated phenomenon as the number of students living outside of their home country has risen to more than three million in the past decade. Governments, regions and institutions have developed new structures and strategies to facilitate and benefit from this worldwide student movement. This research article uses Fairclough’s (1993) notion of critical discourse analysis to explore the relationship between two distinct discourses on foreign students: national-level economic competitiveness and institutional-level student success. A comparative approach examines these discursive events in the four leading, Anglophone destination countries: Australia, Britain, Canada and the United States. The findings suggest that foreign students are objectified as tradable units in the market-driven discourse of economic development with student support literature providing a buffer that limits the critique of the economic discourse. At the same time, potential exists for current events to highlight the tension surrounding the two discourses and provide new opportunities for dialogue.
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 | 0.014 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.015 | 0.035 |
| Scholarly communication | 0.017 | 0.013 |
| Open science | 0.002 | 0.010 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.002 | 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".