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Record W4256318797 · doi:10.47678/cjhe.v48i2.188121

Experiences of Food Insecurity Among Undergraduate Students: “You Can’t Starve Yourself Through School”

2018· article· en· W4256318797 on OpenAlexaffvenueabout
Merryn Maynard, Samantha B. Meyer, Christopher M. Perlman, Sharon I. Kirkpatrick

Bibliographic record

VenueCanadian Journal of Higher Education · 2018
Typearticle
Languageen
FieldHealth Professions
TopicFood Security and Health in Diverse Populations
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsFood insecurityFood securityPsychologyEconomic shortageMental healthAnxietyMedical educationMedicinePsychiatryAgriculture

Abstract

fetched live from OpenAlex

Canadian post-secondary students are vulnerable to food insecurity, yet lack of examination of this issue has prevented identification of policy and program solutions. This mixed-methods study aimed to characterize the experience of food insecurity among undergraduate students by eliciting barriers to food security, strategies used to manage food and money shortages, and perceived implications for health and academic achievement. Surveys and in-depth interviews were conducted with 14 students who demonstrated compromised financial access to food. Students normalized experiences of food insecurity as typical of post-secondary education but expressed anxiety and frustration with financial inaccessibility to healthy food, and described negative implications for their physical and mental health and their ability to perform well in school. Ongoing attempts to adapt or adjust to food insecurity had limited success. Findings highlight the need to challenge the “starving student” ideology, which normalizes the lack of access to healthy food during higher education.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.137
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.112
GPT teacher head0.452
Teacher spread0.340 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations33
Published2018
Admission routes3
Has abstractyes

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