Bibliographic record
Abstract
The number of immigrant and international students in Canada and other Western countries has increased in recent decades. This group of people faces many challenges, especially at the beginning of their entrance to the host country, such as different expectations regarding two different cultures, being away from their family and loneliness, financial problems, language limitations, and racism. As the experiences of these students can affect their satisfaction and success during their academic years, it is essential to explore the experiences of this growing population during their higher education. In this paper, I explore my own experience as a female international student. My first several years in Canada illustrate the everyday struggles I have faced to attain social, cultural, and linguistic development and build a new life in a new country. Using evocative autoethnography as a research methodology has revealed layers of my consciousness by connecting my personal experience to culture. This autoethnographic study presents the reflections of an Iranian female scholar’s experiences in Canadian higher education; it explores how my personal status as an Iranian female scholar, along with social factors, have shaped my academic experiences in Canada.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.014 | 0.009 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".