Barriers to college student food access: a scoping review examining policies, systems, and the environment
Bibliographic record
Abstract
Abstract College student food insecurity (FI) is a public health concern. Programming and policies to support students have expanded but utilisation is often limited. The aim of this study was to summarise the barriers to accessing college FI programming guided by the social ecological model (SEM) framework. A scoping review of peer-reviewed literature included an electronic search conducted in MEDLINE, ERIC, and PubMed databases, with a secondary search in Google Scholar. Of the 138 articles identified, 18 articles met eligibility criteria and were included. Articles primarily encompassed organisational (17/18) level barriers, followed by individual (15/18), relationship (15/18), community (9/18), and policy (6/18) levels. Individual barriers included seven themes: Knowledge of Process, Awareness, Limited Time or Schedules, Personal Transportation, Internal Stigma, Perception of Need, and Type of Student. Four relationship barriers were identified: External Stigma, Comparing Need, Limited Availability Causes Negative Perceptions, and Staff. Ten barrier themes comprised the organisational level: Application Process, Operational Process, Location, Hours of Operation, Food Quality, Food Quantity, Food Desirability or Variety of Food, Marketing Materials, Awareness of the Program, and COVID-19 Restrictions. Two barrier themes were identified at the community level, Public Transportation and Awareness of SNAP, while one barrier theme, SNAP Eligibility and Process, encompassed the policy level. Higher education stakeholders should seek to overcome these barriers to the use of food programmes as a means to address the issue of college FI. This review offers recommendations to overcome these barriers at each SEM level.
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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 | 0.016 | 0.068 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.012 | 0.016 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".