An Ecological Perspective of Chinese International Students’ Experiences of Social Network Development in a Canadian University
Bibliographic record
Abstract
This study explores the experiences of Chinese international doctoral students as they navigate the development of social support networks within a Canadian university, framed through an Ecological Perspective. The research involved six graduate students from China who participated in this qualitative case study. Data was collected through semi-structured interviews. The findings reveal that the surrounding environment was an important factor in the formation and evolution of the participants’ social networks, particularly during the initial stages of their academic journey. The study highlights the critical role of the university’s environment in either facilitating or hindering the establishment of these networks. Moreover, the research underscores the necessity for the university to bolster its support structures to more effectively address the diverse needs of its international student population. This enhancement is essential not only for academic success but also for the overall well-being of the students. The results suggest that social connection, as a fundamental human need, is vital for the mental health and quality of life of students, both in the immediate and long-term contexts. The importance of socializing extends beyond personal well-being, impacting academic performance and integration into the university community. Therefore, fostering robust social support networks is crucial for international doctoral students as they pursue their personal and academic goals.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.033 | 0.012 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.001 | 0.002 |
| 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".