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Record W4406214401 · doi:10.1080/16583655.2025.2449616

Global research trends in zero-waste cities: a comprehensive bibliometric analysis

2025· article· en· W4406214401 on OpenAlex
Han Wang, Bin Zhao, Shaban G. Gouda

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.

Bibliographic record

VenueJournal of Taibah University for Science · 2025
Typearticle
Languageen
FieldEnvironmental Science
TopicMunicipal Solid Waste Management
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsZero (linguistics)Zero wasteEnvironmental scienceRegional scienceEnvironmental planningGeographyWaste managementEngineering

Abstract

fetched live from OpenAlex

Zero-waste cities are one of the important ways to promote resources sustainable development worldwide and have significant implications for promoting the recycling of waste resources and promoting global sustainable development. This study presents a comprehensive bibliometric analysis of zero-waste cities to explore the current research landscape. Web of Science Core Collection (WoSCC), PubMed and Scopus databases were used to retrieve a total of 392 articles containing research on zero-waste cities. These data were analysed by bibliometric methods to draw the research trends and recent advances in zero-waste cities comprehensive overview. The results show that the first article on zero-waste cities was published in 2008, marking the start of research in this area. In 2013, the most cited article was published by Zaman Au et al., and Italy is the country with the most research in this field. Additionally, the scholars and institutions who published the most papers in this field were investigated. Keywords: “circular economy”, “food waste”, “zero waste”, “recycling” and “waste management” remain the most used words in research. Furthermore, the data analysis illustrated that “waste collection” and its related components such as “waste diversion rate” and “waste generation” are emerging topics in zero-waste cities, however, it needs further development and more connections with zero-waste cities. Keywords such as “circular economy”, “sustainable development” and “carbon emissions” may become research hotspots or future trends. Finally, this study presents the future direction of zero-waste cities, thematic focus and research hotspots making a valuable contribution to zero-waste cities field.

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.

Direct model labels (unvalidated)

Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.

Model armCategoriesStudy designConfidence
gemmaBibliometrics
Domain: not available · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: no
Observationallow
gptBibliometrics
Domain: not available · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: no
Other designhigh
models splitAgreement compares identical category sets and study designs across arms.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesBibliometrics
Consensus categoriesBibliometrics
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.571
Threshold uncertainty score0.935

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0760.383
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0020.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.052
GPT teacher head0.354
Teacher spread0.302 · 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