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Record W4288447260 · doi:10.3389/fpsyt.2022.883817

Connecting to nature through community engaged scholarship: Community gardens as sites for collaborative relationships, psychological, and physiological wellbeing

2022· article· en· W4288447260 on OpenAlexaff
Kumara Ward, Son Truong, Tonia Gray

Bibliographic record

VenueFrontiers in Psychiatry · 2022
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicUrban Agriculture and Sustainability
Canadian institutionsDalhousie University
Fundersnot available
KeywordsOutreachScholarshipCommunity buildingCommunity engagementCommunity developmentCommunity cohesionCommunity organizationPublic relationsCommunity psychologyPsychologySociologyPolitical scienceSocial psychology

Abstract

fetched live from OpenAlex

Community gardens are recognized as being associated with a range of benefits for participants that include enhanced outcomes in physical and affective domains and community building. The purpose of this study was to research the impact of the New South Wales Royal Botanic Gardens (RBG) Community Greening (CG) program and to inform the ongoing development of this community outreach program. The organic community partnerships inherent in the design and the relationships between the Community Greening program participants and researchers is examined through the lens of Community Engaged Scholarship (CES). Over a seven-month period, the CG team implemented a community garden development program in six sites. Mixed-method research on the impact of the program found that the community gardening participants experienced positive changes in physical activity, psychological wellbeing and motivation for social engagement, and these outcomes were facilitated as a result of their relationships with members of the CG team. This paper examines how such programs, when explicitly framed as CES, could assist in consolidating nature-based community health and wellbeing programs and further legitimize community partnerships in development of community garden and green spaces as academically sound investigation and socio-economically justified activity. Expansion of this nature-based collaboration model may also enhance community engagement in green exercise, psychological wellbeing and community cohesion, and in turn support advocacy for greener environments locally, regionally and nationally.

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)0.004
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.259
Threshold uncertainty score0.995

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0090.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.007
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 head0.053
GPT teacher head0.292
Teacher spread0.239 · 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

Citations13
Published2022
Admission routes1
Has abstractyes

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