Gender, sexuality, and food access: An exploration of food security with LGBTQIA2S+ university students
Bibliographic record
Abstract
Although research has been limited to date, food insecurity in the United States has been shown to be more pervasive among the lesbian, gay, bisexual, transgender, queer, questioning, intersex, agender, asexual, and Two-Spirit (LGBTQIA2S+) community, affecting millions annually. College and university students also experience statistically significantly higher rates of food insecurity than nonstudents. This research examines food insecurity at the intersection of the LGBTQIA2S+ community and the university and college student population, as told by the community itself. A qualitative, participatory approach and methods of Photovoice and semi-structured interviews with eight self-identified LGBTQIA2S+ university students studying at the University of North Carolina at Greensboro (UNCG) were used to explore the factors influencing participants’ food access. Data were analyzed using thematic decomposition analysis guided by intersectionality and queer theories. LGBTQIA2S+ identities were found to significantly impact food access, which was further influenced by physical, socio-cultural, and political environments. Barriers to food access include experiences with discrimination on and off campus, poor support systems, a lack of full-selection grocery stores on or near campus, religious influences, the stigma associated with needing food assistance, mental and physical health conditions, financial constraints, time limitations, and lacking transportation options. Understanding the intersectionality of LGBTQIA2S+ students’ experiences and providing relevant and effective support is needed to improve equitable access to nutritious and affordable foods. The findings of this research provide novel insights into food insecurity, an issue that is increasingly influencing the health and well-being of LGBTQIA2S+ university students.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".