Bibliographic record
Abstract
In the past few years internationalization has become one of the biggest missions of Canadian post secondary institutions. Thus, the number of visible minority and international faculty members and students has grown significantly in Canadian Universities (Altbach and Knight, 2007). In 2010, international students represented approximately eight percent of full-time undergraduate students in Canada, approximately 18 percent of full-time master’s students, and 23 percent of full-time PhD students (AUCC, 2011). In Canada, the majority of these students come from Asian countries (including Middle East). Among these Asian countries some send far more students other than other. Iran, for example, with a nearly 20% increase from 2010 to 2011, with 3,892 students (1.63% of total IS population in Canada) sits in 9 th place in the top 10 sender countries. This is while currently, Iranian students in Canada are affected differently by the limited relations and political context between two countries, Iran and Canada (Pinch, 2012). While Iranian international students move to Canada with the hopes of a better education and life compared to their home countries, they face social and psychological challenges due to some reasons, such as lack of support, discriminatory policies/attitudes, and prejudice. According to a 2012 BBC World Service poll, only 9% of Canadians have a positive view about Iran, and 81% express a negative view. Such a negative attitude towards their homeland, along with policies and actions that exert pressure to their lives makes Iranian students struggle for their well-being in Canada (e.g. embassy closures both in Iran and Canada). Considering the importance of being attentive to international students’ lives, the important question is “how can researchers, educators, and policy makers help international students’ social and psychological well-being?” I believe the first step in getting a proper response for such a question is to ask “How do international students experience life in a new country/place such as Canada?” This question will take us to the very lives of international students, their social interactions and experiences which shape who they are and how they think. In this paper, I will review and elaborate on some key elements, such as place/space, home, self, power, and agency, which can be helpful for the researchers to analyze and to understand the life and experiences of international students. Benefiting from the case of Iranian international students, I will argue how such understanding will help to promote a space in which international students feel safe and supported in their social and academic lives.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".