The Impact of Government Policy on Higher Education International Student Recruiters
Bibliographic record
Abstract
This paper explores higher education actors involved in the recruitment of internationalstudents and their perceptions of their home country’s government policy on their practice. It examines case study institutions from three countries Canada, Hong Kong, and the United Kingdom. This study shows higher education institutions do not exist in a vacuum and regardless of their location, government policy shapes perceptions for international student recruiters who believe that government policies contribute or hinder their practice. All of the participants, regardless of location, show a high level of awareness of government policy that greatly shapes their strategies. More specifically, recruiters find tensions arising from these policies with government shaping recruitment priorities and restricting or instigating competitive responses, while their institutions do not challenge government policy (enough). The findings suggest that government policies establish the “playing field” for recruiters as they attempt to navigate an increasingly competitive environment but at the same time, these perceptions are highly localized and need to be understood in their individual settings.Keywords:internationalization; government policies; recruiters; students
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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 | 0.013 | 0.020 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.007 |
| Scholarly communication | 0.007 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| 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".