Ideal immigrants in name only? Shifting constructions and divergent discourses on the international student-immigration policy nexus in Australia, Canada, and Germany
Bibliographic record
Abstract
The proposition that international students are not only sojourners but future immigrants has become well established in public policy. While education and immigration policy have become more intertwined, they continue to be analysed as separate spheres of influence. This paper compares Australia, Canada, and Germany, which between them host nearly 20% of all globally mobile students and where a nexus between international student and immigration policy has emerged. Using critical discourse analysis, a comparative case study design and based on a systematic literature review of over 300 studies published from 1990 to 2018, the findings revealed three ostensibly paradoxical discourses, which are discussed using the new term ‘discursive pairings’. First, international students are selected for success but remain vulnerable to policy shifts that may exclude them and cause them to ‘fail’. Second, international students are retained to fill economic shortages, but face difficulties being accepted on the labour market. Third, international students help build national reputation yet have been known to be exploited and subject to discrimination. The contradictions that emerge in the discourses bring into question the ‘ideal immigrant’ framing of international students, demonstrating that their role, acceptance, and ability to integrate into host countries is far from assured.
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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 | 0.017 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.016 | 0.030 |
| Scholarly communication | 0.014 | 0.007 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.001 | 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".