Pursuing intra-country cross-border higher education: an exploration of Macao students’ motivations to study in mainland Chinese universities
Bibliographic record
Abstract
This study explores the motivations of Macao students to pursue intra-country cross-border higher education (HE) at mainland Chinese universities. Data was collected from in-depth interviews with 20 Macao students in mainland Chinese universities, supplemented by the universities’ recruitment and scholarship policies toward SAR students. Informed by a revised ‘push-pull’ model and the notion of migration infrastructures, the findings reveal that societal infrastructures in Macao and mainland China under the ‘One Country, Two Systems’ guiding framework form a push-pull dynamic to shape Macao students’ intra-country cross-border mobility aspirations. Institutional infrastructures mainly manifested as Macao’s uneven HE development and preferential enrolment policies in mainland Chinese institutions further push and pull students to study in the mainland. Finally, students showcase agency in pursuing cross-border HE by strategically responding to these infrastructural influences through individual push-pull factors. The findings implicate on the increasing convergence between Macao and mainland China under the Greater Bay Area (GBA) initiative, as well as its impact on the regionalisation of Chinese HE and Macao’s post-colonial transformation through intra-country cross-border student mobility. Insights into Macao’s context and unique HE system in relation to Chinese HE fill a notable gap. Future research can explore Macao students’ mobility experiences in more depth.
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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 | 0.002 | 0.002 |
| 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 | 0.003 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".