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Introduction

2017· book-chapter· en· W4229586379 on OpenAlexaboutno aff
Julian Agyeman, Caitlín Matthews, Hannah Sobel

Bibliographic record

VenueThe MIT Press eBooks · 2017
Typebook-chapter
Languageen
FieldAgricultural and Biological Sciences
TopicOrganic Food and Agriculture
Canadian institutionsnot available
Fundersnot available
KeywordsPopularityTruckCraftAdvertisingPolitical scienceBusinessMarketingEngineeringGeographyLaw

Abstract

fetched live from OpenAlex

The urban food scape is changing rapidly. Food trucks, which are part of a wider phenomenon of street food vending, are an increasingly common sight in many cities throughout the United States and Canada. With this rise in the popularity of food trucks, the key issue of regulatory conflicts between the state, street food vending and food truck entrepreneurs, and the wider industry as a whole, has risen to the fore. Cities have responded in various ways to increased interest in mobile food vending – some have adopted encouraging and relaxed regulations, some have attempted to harness the momentum to craft a city brand, and some have rigidly regulated food trucks in response to protest by brick-and-mortar competitors. This Introduction frames the volume through its guiding questions and a variety of lenses - community economic development, social justice, postmodernism. The Introduction also outlines the sections of the volume (Democratic vs. Regulatory Practices and Spatial-Cultural Practices) and summarizes the chapters included in each section.

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: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.505
Threshold uncertainty score0.703

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.027
GPT teacher head0.197
Teacher spread0.170 · 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
GenreOther

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
Published2017
Admission routes1
Has abstractyes

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