Food insecure student clients of a university‐based food bank have compromised health, dietary intake and academic quality
Bibliographic record
Abstract
Aim University and college students in wealthy countries may be vulnerable to financial food insecurity. If food insecure students have suboptimal health, their ability to learn and excel in their education could be compromised. This Canadian study examined the relationship of food security status to diet and self‐perceived health and academic quality among students receiving emergency food hampers from the Campus Food Bank at University of Alberta. Methods A convenience sample of 58 students completed a survey. Results Of participating students, 10.3% were food secure, 44.8% were moderately food insecure and 44.8% were severely food insecure. Overall, 32.8% rated their general health as fair/poor, 27.6% rated their mental health as fair/poor and 60.3% indicated at least one adverse academic outcome of not having enough money for food. Compared to other participating students, students with severe food insecurity had a greater likelihood of fair/poor general health (odds ratios (OR) 4.03, 95% confidence intervals (CI) 1.10–14.78); fair/poor mental health (OR 4.96, 95% CI 1.28–19.19); being unable to concentrate in class or during an exam (73.1% vs 40.6%, χ2 = 6.12, P = 0.013); relying on food hampers (34.6% vs 9.7%, χ2 = 5.57, P = 0.018); and, consuming fewer daily fruits, vegetables and legumes (2.12 vs 2.97 cup equivalents, P = 0.009). Conclusions Food insecurity compromises students’ health, diet and academic quality. Campus food banks are not the solution to student hunger. Governmental and university‐based programmes and policies are needed to improve the food security situation of university students.
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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".