Bibliographic record
Abstract
Abstract This essay reviews Parallel Societies of International Students in Australia (Gomes, Catherine. 2021. Parallel Societies of International Students in Australia: Connections, Disconnections, and a Global Pandemic , 1st ed. United Kingdom: Routledge), International Students at US Community Colleges (Malveaux, Gregory F., and Krishna Bista, eds. 2021. International Students at US Community Colleges Opportunities, Challenges, and Successes . London: Routledge), and International Students from Asia in Canadian Universities (Kim, Ann H., Elizabeth Buckner, and Jean Michel Montsion, eds. 2023. International Students from Asia in Canadian Universities : Institutional Challenges at the Intersection of Internationalization, Inclusion, and Racialization . 1st ed. New York: Routledge). Collectively, the books elucidate the social and institutional conditions that govern the experiences and coping strategies of international students in three popular study-abroad destination countries: the United States, Canada, and Australia. Through interdisciplinary lenses (e.g., policy analysis, critical race theory, and media ethnography), they examine the lived experiences of international students in terms of mobility, exclusion, and adaptation, highlighting the disjunctures between internationalization rhetoric and practice.
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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 | 0.005 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.009 | 0.045 |
| Scholarly communication | 0.012 | 0.011 |
| Open science | 0.001 | 0.010 |
| Research integrity | 0.002 | 0.003 |
| 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".