A Comparison of Characteristics and Food Insecurity Coping Strategies between International and Domestic Postsecondary Students Using a Food Bank Located on a University Campus
Bibliographic record
Abstract
PURPOSE: We compared food insecurity status, coping strategies, demographic characteristics, and self-rated health of international and domestic postsecondary students requesting emergency food hampers from a campus food bank (CFB). METHODS: We collected data from a cross-sectional convenience sample of domestic and international students who accessed the CFB at the University of Alberta. RESULTS: Food insecurity was prevalent (international students: n = 26/27 (96.2%), domestic students: n = 31/31 (100%)). Compared with their domestic peers, international students were less likely to rate their mental health negatively (14.8% vs 38.7%, P = 0.04). The primary income source was government loans (54.8%) for domestic students and research assistantships (33.3%) for international students. To cope with not having enough money for food, the majority of both student groups delayed bill payments or buying university supplies, applied for loans or bursaries, purchased food on credit, or worked more. International students were less likely to ask friends or relatives for food (48.1% vs 77.4%, P = 0.02). CONCLUSIONS: Domestic and international students mostly used similar coping strategies to address food insecurity; however, they paid for their education using different income sources. Distinct strategies for international and domestic students are required to allow more students to cover their educational and living expenses.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".