From India to Canada: An Autoethnographic Account of an International Student’s Decision to Settle as a Self-Initiated Expatriate
Bibliographic record
Abstract
International students can be a source of skilled workers for many industrialized countries with an aging population. However, it is unclear if international students would stay after completing their studies, given booming economies in their home countries. The present paper explores the decision processes international students make when contemplating whether to stay or return home after completing their studies. The paper is based on an autoethnographic account of an international student who studied in Canada, and follows her journey as an international student through to settlement as a self-initiated expatriate. Initially, personal factors (such as family encouragement), public policy, and employer practices "pushed" the student to repatriate back to her country of origin after her studies. However, personal ambitions (such as travel and career development opportunities) and prospects for a better life "pulled" her back to Canada. Personal agency and positive experiences also contributed to her adjustment and success as a self-initiated expatriate. The present paper adds to existing literature on the "push" and "pull" dynamic of international student retention in the host country. It further enhances our understanding of why international students decide to remain in the country following the completion of their studies.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.031 | 0.010 |
| Scholarly communication | 0.007 | 0.002 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.002 | 0.007 |
| 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".