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Record W1590922292 · doi:10.15353/cfs-rcea.v2i1.23

Campus gardens: Food production or sense of place?

2015· article· en· W1590922292 on OpenAlexvenueno aff
Natalee Ridgeway, June I. Matthews

Bibliographic record

VenueCanadian Food Studies / La Revue canadienne des études sur l alimentation · 2015
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicUrban Agriculture and Sustainability
Canadian institutionsnot available
FundersDirectorate for Biological Sciences
KeywordsSense of placeSustainabilityPopulationSense of communitySociologyExperiential learningPublic relationsPlace attachmentPsychologyPedagogyMarketingBusinessPolitical scienceSocial scienceSocial psychologyEcology

Abstract

fetched live from OpenAlex

Campus gardens can provide opportunities for experiential learning and enhanced physical and mental health; however, they require substantial commitments of time, money, and effort. This formative evaluation explored the perspectives of a university population on the establishment of a campus garden prior to its implementation. Phase 1 involved an electronic survey of the entire population at a small university (N=1300). Phase 2 consisted of 11 in-depth interviews with survey respondents who were interested in furthering the dialogue. The majority (85%) of the 415 individuals who responded to the survey and all interviewees supported the idea of a campus garden. Compared to a shared/community garden or rental plot, participants preferred a low-maintenance forest garden. Food production was secondary to protection of the natural environment and providing a space for rest and reflection. Participants’ sense of community, combined with knowledge of the university’s history, mission, and values, reflected a strong sense of place, a key component of social sustainability. Perhaps it is time to consider alternate options to traditional community gardens on university campuses. This research suggests that forest gardens, with their low-maintenance approach to food production and their potential to promote social sustainability through an enhanced sense of place, may be a good place to start.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.929
Threshold uncertainty score0.945

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.065
GPT teacher head0.229
Teacher spread0.164 · 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 designQualitative
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

Citations8
Published2015
Admission routes1
Has abstractyes

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