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Record W3158143342 · doi:10.1007/s12132-021-09417-9

Integrating Food Sensitive Planning and Urban Design into Urban Governance Actions

2021· article· en· W3158143342 on OpenAlexfundno aff
Gareth Haysom

Bibliographic record

VenueUrban Forum · 2021
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicOrganic Food and Agriculture
Canadian institutionsnot available
FundersEconomic and Social Research CouncilDepartment of Science and Technology, Ministry of Science and Technology, IndiaSocial Sciences and Humanities Research Council of CanadaUniversity of the Western CapeUniversity of PretoriaInternational Development Research Centre
KeywordsHuman geographyCorporate governanceUrban planningEnvironmental planningUrban densityUrban designRegional scienceBusinessEconomic geographyPolitical scienceGeographyCivil engineeringEngineering

Abstract

fetched live from OpenAlex

Food access, stability and utilisation are key dimensions of food security at an urban scale. When the majority resided in rural areas, and lived predominantly agrarian lifestyles, it made sense for the state to govern food security through national agricultural ministries, focusing predominantly on the availability dimension of food security. With the transition to a majority urban world, coupled with the food security challenges currently experienced in urban areas, specifically in Africa, these historical policy and governance structures are increasingly inadequate in responding to essential food and nutrition needs. Problematically, urban areas, and specifically urban managers, cite unfunded mandates, and absent authority, as the reasons for not engaging food and nutrition governance responses. This paper argues that this is a false position. Drawing on recent data from household food security and poverty surveys, the paper calls for new and expanded planning and design approaches at the urban scale. The paper argues that spatial planning and urban design principles and actions provide an immediate and effective means through which to engage urban food system questions. Importantly these actions are essential to the transition from the current piecemeal project responses to urban food system inadequacies. Food sensitive planning and urban design is offered as a specific approach that could assist in programming food system-related challenges at the urban scale, responding to conceptual, analytical, organisational and design related dimensions of planning, and in so doing offering a longer term, systematic response to urban food insecurity.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.018
metaresearch head score (Gemma)0.010
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.018
Threshold uncertainty score0.093

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0180.010
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.002
Science and technology studies0.0070.033
Scholarly communication0.0130.007
Open science0.0020.012
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0060.000

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 head0.020
GPT teacher head0.207
Teacher spread0.187 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
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

Citations28
Published2021
Admission routes1
Has abstractyes

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