Failing to succeed ? The role of migration in the reproduction of social advantage amongst young graduates in Hong Kong
Bibliographic record
Abstract
This paper attempts to unpack the role of failure, and subsequent international mobility, in affecting employment outcomes for ‘overseas educated’ university graduates in Hong Kong. It draws upon extensive fieldwork in Hong Kong and Canada, to scrutinise the link between international credentials and migration, asking : do experiences of living abroad – for schooling and the whole of a university education – confer distinction and subsequent social advantage upon already privileged individuals and their families, offsetting previous academic “failure” ? If so, then why does this process of valorisation occur ? In much of the extant literature on international education, the advantages bestowed upon internationally mobile students are taken for granted. In contrast, this paper begins with the premise that a ‘local’ university degree is widely considered significantly superior to one acquired abroad. Despite this, however, graduates educated overseas are clearly advantaged in many ways when they return to Hong Kong to find work. The analysis of the data shows that the cultural capital and social capital developed through living abroad and attending an overseas higher education institution override, in various ways, the inherent value of a local university degree. The paper contributes to wider debates around the role of international education in the reproduction of privilege and the continuation of class inequalities in educational outcomes.
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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 | 0.001 | 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 | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| 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".