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Record W3178685281

Student Food Insecurity Campus Readiness Assessment: An Analysis of Campus Responses to Student Food Security Across Canadian Universities

2021· article· en· W3178685281 on OpenAlexaboutno aff
Alesandros Glaros, Jill MacIntyre, Sam Laban, Merryn Maynard

Bibliographic record

VenueThe Atrium (University of Guelph) · 2021
Typearticle
Languageen
FieldHealth Professions
TopicFood Security and Health in Diverse Populations
Canadian institutionsnot available
Fundersnot available
KeywordsFood insecurityFood securityBusinessPsychologyGeographyAgriculture
DOInot available

Abstract

fetched live from OpenAlex

The Student Food Insecurity Campus Readiness Assessment supports emerging efforts to galvanize Canadian campus communities to take action in addressing student food insecurity (SFI). The readiness assessment analyzes existing responses to student food insecurity on individual campuses, and provides insights into how the sector as a whole is responding to SFI. It was completed as part of “Promoting Food Security in Higher Education,” a collaboration between Meal Exchange and staff and faculty at the University of British Columbia, the University of Guelph, McMaster University and the University of Ottawa. This collaboration is a reflection of their own efforts to address student food insecurity and also a response to broader attention the issue has received in recent years, including the growing volume of research, news articles and the formation of a number of campus food security committees.

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 imitation

Not 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.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.976
Threshold uncertainty score0.171

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0030.005
Science and technology studies0.0040.001
Scholarly communication0.0020.001
Open science0.0010.003
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 head0.069
GPT teacher head0.407
Teacher spread0.338 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations0
Published2021
Admission routes1
Has abstractyes

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