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Record W4282050426 · doi:10.1186/s42854-022-00036-6

A bibliometric analysis of urban food security

2022· article· en· W4282050426 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueUrban Transformations · 2022
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicUrban Agriculture and Sustainability
Canadian institutionsUniversity of Waterloo
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsFood securityField (mathematics)Data scienceMetadataComputer scienceGeographyWorld Wide Web

Abstract

fetched live from OpenAlex

Abstract The study of urban food security has evolved dramatically over the past few decades. This evolution has been punctuated, and catalyzed, by insights into the dynamic transformation of food systems in cities. The evolution of this field, as revealed by its scholarly writings, provides an important vantage point for understanding both the dynamic transformation of the urban food system as well as the lens through which that transformation has been understood. This investigation adopted a bibliometric methodology, blending quantitative and qualitative analytical techniques, to assess the dynamic evolution of the literature over time. This methodology included a quantitative analysis of the metadata for 162 publications on urban food security. The results of this analysis provided an overview of research progress, historical and evolutionary trends, geographic disparities, keyword distribution, networks of collaboration, and key thematic foci. The quantitative analysis is complemented with a qualitative examination of top publications in the field. The results present a historical narrative of the evolution of urban food security research. In particular, the results indicate that the field has diversified its foci along key distinctions in food access and supply. The findings also identify common strategies and challenges inherent to the governance of urban food systems. In summary, this investigation provides a unique vantage point for discovering the evolution of urban food security and the perspectives that have defined that evolution.

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 categoriesBibliometrics, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.169
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0050.174
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.013
GPT teacher head0.206
Teacher spread0.193 · 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