A bibliometric analysis of urban food security
Bibliographic record
Abstract
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.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.009 | 0.065 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.191 | 0.292 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".