Confronting and Reimagining the Orientation of International Graduate Students: A Collaborative Autoethnography Approach
Bibliographic record
Abstract
This paper uses lived experiences to critically examine the orientation of international graduate students at research-intensive Canadian universities. We, five co-authors, embody diverse ethnic, racial, sexual, religious, national, and gender identities, yet are all (or have been) international graduate students in Canada. Through collaborative autoethnography, we destabilize the notion of “orientation.” We argue that international student orientation should be understood as a fluid, ongoing process rather than one with rigid boundaries and timelines. Furthermore, orientation programming should more deeply consider the intersecting identities and positionalities of international students as multifaced individuals, as well as the implicit expectations of one-way “integration” into settler-colonial Canadian society. We suggest a different approach to orientation and offer a conceptual framework to guide future practice, highlighting the role universities play in not only supporting students academically but also in (im)migrant settlement.
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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 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.015 | 0.030 |
| Scholarly communication | 0.010 | 0.004 |
| Open science | 0.002 | 0.010 |
| Research integrity | 0.002 | 0.005 |
| 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".