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Record W2527630831

Universities and Sustainable Food Practices: An International Comparison Along the Pacific Coast of North America

2016· article· en· W2527630831 on OpenAlexaboutno aff
Alexandra Schulte

Bibliographic record

VenueTopSCHOLAR (Western Kentucky University) · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicSustainability in Higher Education
Canadian institutionsnot available
FundersUniversity of Alaska Anchorage
KeywordsGeographyOceanographyFisheryPolitical scienceGeologyBiology
DOInot available

Abstract

fetched live from OpenAlex

My research project examined sustainable practices in relation to food sources at three universities located along the Pacific Coast of North America. The academic institutions were the University of Alaska Anchorage (UAA), the University of California Santa Barbara (UCSB), and the University of British Columbia (UBC) in Vancouver. These schools were selected because while they each foster an abundance of “local” foods and food industries, they represent different stages in the three pillars of sustainability for food practices. My project sought to understand the role of each institution in building a local and sustainable food culture at each university. I analyzed how the food services at and near the institutions reflect the food and nutritional needs and wants of the student body, faculty, and staff of academic institutions and the availability of foods (e.g., healthy, organic, and sustainable) in each area. Using qualitative data acquired through interviews and source-based literature, I classified the three universities in relation to the three pillars of sustainability, namely economic, social, and environmental. UAA was at an early stage of sustainability achievement while UBC was the most developed. In comparison, I evaluated Western Kentucky University (WKU) as situated between UAA and UCSB. Key steps to successful sustainability of food resources include creating local and regional food resources, engaging students, faculty and administrators, and developing an economically feasible institutional vision. Institutions of higher learning have a strong influence on their region and with forethought and planning, they can serve as drivers of sustainable food systems.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.697
Threshold uncertainty score0.614

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.003
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.028
GPT teacher head0.305
Teacher spread0.277 · 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.

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
Published2016
Admission routes1
Has abstractyes

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