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Urban Farming Movement

2016· book-chapter· en· W2511432567 on OpenAlex
Pierluigi Nicolin

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.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueAdvances in media, entertainment and the arts (AMEA) book series · 2016
Typebook-chapter
Languageen
FieldAgricultural and Biological Sciences
TopicUrban Agriculture and Sustainability
Canadian institutionsnot available
Fundersnot available
KeywordsBeijingUrban agricultureGeographyAgricultureScale (ratio)PhenomenonMovement (music)Work (physics)Urban ecosystemAgricultural productivityUrban planningChinaCivil engineeringCartographyEngineering

Abstract

fetched live from OpenAlex

The expression “urban agriculture” refers to the emergence in many cities of areas cultivated by farmers who distribute the fruits of the land they work in the environs of the zone of production. The movement, born in response to a range of real needs, has become a global phenomenon, and has taken on an organized form in a large number of cities: from Mumbai to Beijing, London, New York, Detroit, São Paulo, Rosario, Vancouver, Tokyo, San Francisco, etc. The urban farming movement, with its production of food, its educational aims and the idea of creating sustainable situations, has been able to take root in many cities and metropolises as it is closely integrated with the urban ecosystem. For the most part it is the poor and women who, working on small farms located both inside and outside the city, are nurturing this politico-cultural movement. Their agricultural settings are creating new and interesting landscapes that need to be analyzed from an aesthetic perspective as well for the influence that they might have on contemporary landscape architecture. The phenomenon could have repercussions on the visual conventions of the urban and suburban environment and even affect the behavior and lifestyles of city dwellers should it develop on a larger scale.

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)0.000
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: Other · Consensus signal: Other
Teacher disagreement score0.938
Threshold uncertainty score0.701

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.005
GPT teacher head0.184
Teacher spread0.178 · 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