MétaCan
Menu
Back to cohort
Record W4411633657 · doi:10.1111/gec3.70041

Positive Futures for Urban Agriculture in Asia? A Review

2025· review· en· W4411633657 on OpenAlexaff
Melody Lynch, Sarah Turner

Bibliographic record

VenueGeography Compass · 2025
Typereview
Languageen
FieldAgricultural and Biological Sciences
TopicUrban Agriculture and Sustainability
Canadian institutionsMcGill University
Fundersnot available
KeywordsFutures contractGeographyEconomic geographyAgricultureRegional scienceEnvironmental planningEconomicsFinancial economicsArchaeology

Abstract

fetched live from OpenAlex

ABSTRACT Many governments in Asia have recently started formulating policies for urban agriculture (UA), despite challenges regarding food safety, land access, and equity. In this paper, we systematically review the literature on the health, economic, social, and political dimensions of UA in South, East, and Southeast Asia. Our review reveals that key motivations and attitudes framing UA initiatives are distinct to this region, with food safety concerns being a stronger motivating force than ecological benefits or social justice. Heightened skepticism of dominant food systems in this region is contributing to new cultural agricultural geographies. An ideological shift is also occurring whereby agriculture is beginning to be perceived of as a more‐than‐rural activity. Nonetheless, we reveal that narrow and often negative perceptions of agriculture in Asia limits the types and extent to which UA occurs. Land access and tenure security are among the greatest barriers to participation in UA. Our review demonstrates that government support for UA has not always been effective, and we outline how capacity building and leveraging local knowledges have been more effective strategies for achieving socio‐ecological benefits through UA than technological innovation. Overall, UA's benefits are context dependent and vary across lines of difference related to ethnicity, gender, class, and age. This review will serve as a guidepost for future research and policies aiming to support sustainable and equitable UA in the region, and possibly beyond.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.734
Threshold uncertainty score0.898

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0000.003
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
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 head0.015
GPT teacher head0.264
Teacher spread0.249 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
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 routes1
Has abstractyes

Explore more

Same venueGeography CompassSame topicUrban Agriculture and SustainabilityFrench-language works237,207