Correlates of Food Insecurity Among Undergraduate Students
Bibliographic record
Abstract
Food insecurity has been identified as an issue among postsecondary students. We conducted this study to describe the level of food insecurity in a sample of university students with a particular interest in the effect of marginalization. A cross-sectional survey was conducted using a volunteer sample of 3,636 undergraduate students (44% participation rate) at one BC university campus between February and May 2017. Forty-two percent (n=1479) of respondents were classified as experiencing food insecurity. Among those who were food insecure 58% (n=891) were female. Logistic regression analysis indicated that females, students living on campus, those with a diverseability (developmental, physical, or other diversability), individuals self-reporting as belonging to a visible minority and international students were more likely to experience food insecurity. When adjusted for sex, years on campus, and living situation, students who reported experiencing two or more forms of marginalization were 2.52 times more likely to be food insecure compared to students who do not report any form of marginalization. This study further supports concerns about high levels of food insecurity among university students in Canada. In particular, the findings highlight the risk for food insecurity among students who are already vulnerable to socio-economic inequity due to belonging to marginalized groups. Efforts to promote student wellbeing on university campuses need to address food insecurity by addressing system-level factors to equalize the field for all students at risk for food insecurity.
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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 | 0.003 |
| 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) | 0.002 | 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".