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Record W4405465538 · doi:10.1016/j.envsci.2024.103972

A systems thinking approach to examine local food systems planning through a climate-biodiversity-health lens: A Comox Valley case study

2024· article· en· W4405465538 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueEnvironmental Science & Policy · 2024
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicOrganic Food and Agriculture
Canadian institutionsRoyal Roads University
FundersSocial Sciences and Humanities Research CouncilSocial Sciences and Humanities Research Council of Canada
KeywordsBiodiversityEnvironmental planningEnvironmental resource managementLens (geology)Food systemsClimate systemGeographyEnvironmental scienceBusinessClimate changeFood securityEcologyGeologyBiology

Abstract

fetched live from OpenAlex

Food systems are highly vulnerable to the effects of anthropogenic climate change and environmental degradation. At the same time, food systems contribute significantly to the production of greenhouse gases that negatively impact ecosystems. Such a vicious cycle of cause and effect demands a transition to sustainable food systems, and this is best done through integrated planning and policy perspectives that tackle interconnected socioeconomic and environmental concerns and goals. This research applies systems thinking to map relationships among food systems planning and other sustainability priorities, namely those related to climate, biodiversity, and health. The study engaged stakeholders in the Comox Valley region, British Columbia, to develop a causal loop diagram, which was subsequently analyzed using the Girvan-Newman community detection algorithm to identify closely connected nodes or 'clusters'. The results of this work provide a comprehensive understanding of how local food systems' challenges and opportunities connect and integrate with other local and regional sustainability objectives. The research identified 123 systems nodes, which were organized into five categories: food, climate, biodiversity, health, and governance. The community detection method was applied to reveal 15 clusters among these nodes. The methodology employed in this research, integrating the development of a causal loop diagram and applying community detection, is novel and contributes to the growing body of literature advocating for an integrated planning approach to address the complex challenges facing local and regional food systems. • The Climate-Biodiversity-Health nexus is integral to food system planning • An integrated planning process involves stakeholders from various sectors • Systems approach reveals links between socio-environmental and governance components • Systems approach finds interventions and fosters collaboration among stakeholders • Community detection uncovers system structure and aids decision-making

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.

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: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.394
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0020.000
Scholarly communication0.0010.001
Open science0.0010.001
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 head0.038
GPT teacher head0.248
Teacher spread0.211 · 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