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Record W4407201732 · doi:10.1139/er-2024-0018

Community engagement in nature-positive food systems programming and research in East and Southern Africa: a review

2025· review· en· W4407201732 on OpenAlexafffundvenue
Melanie Zurba, Yuge Wang, Michael Salomons, Aden Morton-Ferguson

Bibliographic record

VenueEnvironmental Reviews · 2025
Typereview
Languageen
FieldAgricultural and Biological Sciences
TopicOrganic Food and Agriculture
Canadian institutionsBusiness Development Bank of CanadaDalhousie University
FundersGlobal Affairs Canada
KeywordsGeographyFood securityFood systemsEcologyEnvironmental planningEnvironmental resource managementBiologyEnvironmental scienceAgriculture

Abstract

fetched live from OpenAlex

There is strong and rapid momentum in the international conservation space toward “nature-positive” programs in development spaces. These food programs and/or interventions exist in a variety of social and geographic contexts. Alongside the movement toward nature-positives systems is a need to work toward social justice, community engagement, and collaboration in the delivery of new programs and approaches. To support the transition and future research in this area we conducted a scoping review that focused regionally on East and South Africa. The focus on these regions was determined based on their long histories of food programs and increasing attention on new nature-positive food programming. Key findings from our scoping review include clear links between actors at different regional scales, such as international agencies, research institutes, governments, and local NGOs; significant barriers to community engagement opportunities in nature-positive food systems seem to fit within three distinct categories (social, environmental, and political/strategic); and lastly, we find that the outcomes of nature-positive food system programs include benefits for the natural environment (i.e., environmental conservation and management, wildlife conservation, and soil quality improvement) as well as benefits for local communities (i.e., alleviating social issues such as poverty, food insecurity, and gender inequality).

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesResearch integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.984
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.003
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 head0.126
GPT teacher head0.314
Teacher spread0.188 · 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 designOther design
Domainnot available
GenreReview

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

Citations1
Published2025
Admission routes3
Has abstractyes

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