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Planning the urban foodscape: policy and regulation of urban agriculture in Aotearoa New Zealand

2021· article· en· W6920768709 on OpenAlexaff

Bibliographic record

VenueFigshare · 2021
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicUrban Agriculture and Sustainability
Canadian institutionsMcMaster University
Fundersnot available
KeywordsAotearoaFood sovereigntyZoningUrban agricultureUrban planningUrban policyAgricultureLand usePace

Abstract

fetched live from OpenAlex

Policy support for urban agriculture (UA) has increased internationally in the past decade, driven by factors such as urban decay, food insecurity, climate change and disasters, self-determination efforts and the Covid-19 pandemic. To date, there has been little analysis of the emergent practices across different cities in Aotearoa New Zealand. To address this gap, we examine key aspects of UA in Aotearoa and assess the application of local plans and regulation to determine how UA is defined and treated in the four most populous cities. The results reveal a lack of specific attention to and policy direction for UA. This vacuum is compounded by purpose-driven zoning typologies, restrictive resource use controls, scant provision for Māori food practices and a failure to keep pace with the changing forms of UA. The results identify the need for cities to review and clarify provision for UA, to create greater certainty and where appropriate, facilitation of food sovereignty and diverse urban foodscapes. Glossary of Māori terms: Ahikā: continuous occupation of territory; Ahuwhenua: agriculture; Huawhenua: horticulture; Kai: food; Kaitiakitanga: guardianship; Kaupapa Māori: Māori customary practice; Kūmara: sweet potato; Mahinga kai/hauanga kai: the customary and contemporary activity of and the place of harvesting, collection, hunting and gathering of food resources and other materials; Mākete: market; Mana whenua: the people of the land who have mana or customary authority - their historical, cultural and genealogical heritage are attached to the land and sea; Māra kai: food garden; Marae: open area in front of the meeting house, where formal greetings and discussions take place. Includes the grounds and buildings around the marae; Mātauranga Māori: the body of knowledge originating from Māori ancestors, including the Māori world view and perspectives, Māori creativity and cultural practices; Pākehā: New Zealander of European descent; Papakāinga: a settlement or village which has genealogical connections to that land; Māra rongoā: medicinal garden; Tangata whenua: indigenous people - people born of the land; Te Tiriti o Waitangi: Te reo Māori text of the Treaty of Waitangi; Tikanga: protocol - the customary system of values and practices that have developed over time and are deeply embedded in the social context; Whānau: extended family; Whare hoko: the use of land and/or buildings to provide readily accessible retail activities and commercial services required on a day to day basis Glossary sources: Te Aka Online Māori Dictionary, Auckland Unitary Plan 2016, Christchurch District Plan 2017.

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)0.002
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.589
Threshold uncertainty score0.827

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0020.004
Scholarly communication0.0030.002
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.021
GPT teacher head0.225
Teacher spread0.204 · 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 designNot applicable
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

Citations0
Published2021
Admission routes1
Has abstractyes

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