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Record W3216582985 · doi:10.1002/ieam.4558

The sustainable agriculture imperative: A perspective on the need for an agrosystem approach to meet the United Nations Sustainable Development Goals by 2030

2021· article· en· W3216582985 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.

Bibliographic record

VenueIntegrated Environmental Assessment and Management · 2021
Typearticle
Languageen
FieldEnvironmental Science
TopicAgriculture Sustainability and Environmental Impact
Canadian institutionsUniversity of WindsorUniversity of Guelph
Fundersnot available
KeywordsAgricultureFood securityNatural resource economicsSustainable developmentAgricultural productivityBusinessSustainabilityEcosystem servicesEnvironmental resource managementSustainable agricultureDPSIRSustainable Agriculture Innovation NetworkEnvironmental planningEnvironmental scienceEconomicsGeographyEcosystemPolitical scienceEcology

Abstract

fetched live from OpenAlex

Abstract The development of modern, industrial agriculture and its high input–high output carbon energy model is rendering agricultural landscapes less resilient. The expected continued increase in the frequency and intensity of extreme weather events, in conjunction with declining soil health and biodiversity losses, could make food more expensive to produce. The United Nations has called for global action by establishing 17 sustainable development goals (SDGs), four of which are linked to food production and security: declining biodiversity (SDG 15), loss of ecosystem services and agroecosystem stability caused by increasing stress from food production intensification and climate change (SDG 13), declining soil health caused by agricultural practices (SDGs 2 and 6), and dependence on synthetic fertilizers and pesticides to maintain high productivity (SDG 2). To achieve these SDGs, the agriculture sector must take a leading role in reversing the many negative environmental trends apparent in today's agricultural landscapes to ensure that they will adapt and be resilient to climate change in 2030 and beyond. This will demand fundamental changes in how we practice agriculture from an environmental standpoint. Here, we present a perspective focused on the implementation of an agrosystem approach, which we define to promote regenerative agriculture, an integrative approach that provides greater resilience to a changing climate, reverses biodiversity loss, and improves soil health; honors Indigenous ways of knowing and a holistic approach to living off and learning from the land; and supports the establishment of emerging circular economies and community well-being. Integr Environ Assess Manag 2022;18:1199–1205. © 2021 SETAC KEY POINTS The agrosystem approach promotes regenerative agriculture, an integrative approach that can provide greater resilience to a changing climate, reverse biodiversity loss, and improve soil health. The agrosystem approach honors Indigenous ways of knowing and a holistic approach to living off and learning from the land The agrosystem approach supports the establishment of emerging circular economies and community well-being

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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.631
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0040.000
Scholarly communication0.0010.000
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 head0.008
GPT teacher head0.247
Teacher spread0.240 · 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