Feeding the gap: A comprehensive bibliometric review of food bank research
Bibliographic record
Abstract
This study presents a comprehensive bibliometric analysis of the food bank literature, highlighting the role of food banks in addressing the global challenges of food insecurity and waste. Food banks operate at the nexus of waste reduction and hunger alleviation, collecting excess food and distributing it through a network of charities to communities in need.This study traces the scholarly evolution of food banks, highlighting key trends, contributors, and thematic clusters from 1997 to 2022. Bibliometric mapping tools are used to examine the dynamic research landscape and identify influential authors, journals, and the geographical spread of contributions. The analysis reveals a significant increase in research output post-2015, correlating with the global agenda towards Sustainable Development Goals. The United States and Canada have emerged as leading contributors, with the research network indicating robust international collaborations.Thematic analyses through keyword co-occurrence, co-citation, and bibliographic coupling uncover the multidisciplinary nature of food bank studies, encompassing public health, social policy, and environmental sustainability. Key findings from cocitation and bibliographic coupling analyses indicate a shift towards a holistic understanding of food banks' roles within societal and policy frameworks, emphasizing health outcomes, operational strategies for managing food waste, and the sociopolitical impacts of austerity measures. This paper underscores the importance of continued interdisciplinary research and innovative policy formulations to ensure that food banks effectively address the complex dynamics of food insecurity.Despite its limitations, this study offers a robust foundation for future exploration in this field, providing support for broader inclusivity and diversity in research.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 0.000 |
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.
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 teacher head, 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".