Stress, Burnout, Coping strategies and wellbeing among International students in Canada
Bibliographic record
Abstract
Abstract This major paper explores the adaptive and maladaptive coping strategies employed by international students in Canadian universities, particularly in Ontario, to navigate academic and cultural challenges. The researcher aims to expand the understanding of how these students adapt to academic burden, with a focus on their coping resources and strategies for positive adaptation. Key themes identified through a literature review include social and psychological support, managing culture shock, understanding Canadian pedagogy, and various coping mechanisms. Additionally, the study examines the academic support services, non-academic resources, and recreational opportunities available at the University of Windsor which helped cope better. The findings highlight that university provide instrumental support to help international students cope, which aligns with prior research. Traditional coping models, such as those proposed by Lazarus and Folkman, alongside culturally relevant frameworks by Dutton,2011 were integral to understanding students' experiences. The paper emphasizes the importance of holistic wellness strategies and culturally adaptive pedagogical practices to better equip international students with the tools necessary to overcome academic and life challenges in Canada.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.009 | 0.001 |
| Scholarly communication | 0.003 | 0.000 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| 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".