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Physically apart but socially connected: Lessons in social resilience from community gardening during the COVID-19 pandemic

2022· article· en· W4220812174 on OpenAlexaboutno aff
Neelakshi Joshi, Wolfgang Wende

Bibliographic record

VenueLandscape and Urban Planning · 2022
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicUrban Agriculture and Sustainability
Canadian institutionsnot available
Fundersnot available
KeywordsRespite careCommunity resiliencePandemicCoronavirus disease 2019 (COVID-19)SociologyPsychological resilienceWork (physics)Resilience (materials science)EthnographyPublic relationsSocioeconomicsPolitical sciencePsychologyResource (disambiguation)NursingSocial psychologyMedicineEngineering

Abstract

fetched live from OpenAlex

Urban green spaces, like community gardens, received increased attention during the COVID-19 pandemic. Drawing from an ethnographic study on participating in community garden activities in Edmonton, Canada and inputs from 194 gardeners and 21 garden coordinators, this paper captures the experiences of creating community during a pandemic. Garden coordinators had to rethink and rework their operating styles in keeping participants physically apart but socially connected. Participants confirmed that garden activities provided respite from the pandemic restrictions. Findings also indicate that some participants missed group activities like work bees and potlucks while others were able to re-create community in digital spaces and in chanced and informal interactions. This study draws from and subsequently contributes to the existing literature on social resilience provided by community gardens during and after a crisis event. It also provides policy recommendations on how the city administration can help facilitate garden activities during times of disruptions.

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 categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.028
Threshold uncertainty score0.998

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 studies0.0030.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.043
GPT teacher head0.264
Teacher spread0.222 · 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

Citations55
Published2022
Admission routes1
Has abstractyes

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