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Urban Metabolisms, Hinterland Connections

2025· reference-entry· en· W4411464679 on OpenAlexaff
Andrew Watson

Bibliographic record

Venuenot available
Typereference-entry
Languageen
FieldEnvironmental Science
TopicSustainability and Ecological Systems Analysis
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsUrban metabolismScope (computer science)Resource (disambiguation)SustainabilityMaterial flow analysisMetaphorPoliticsSociologyGeographyRegional scienceEnvironmental planningEconomic geographyEcologyUrban planningPolitical scienceUrban densityBiologyComputer science

Abstract

fetched live from OpenAlex

Urban and rural environmental histories are often treated separately. However, environmental historians, social ecologists, sociologists, geographers, ecological economists, and sustainability studies scholars have adopted an urban metabolism approach to study the relationships between cities and their resource hinterlands, watersheds, and waste sinks. Historical urban metabolism research tends to be fairly interdisciplinary, informed by methods developed by social scientists, and draws heavily on long time series quantitative sources that allow scholars to recreate and evaluate the flow of material and energy into, through, and out of defined urban system boundaries. However, there are many studies that use the concept of metabolism as a metaphor and rely mainly on qualitative sources to provide a social, political, and cultural analysis of the relationships between cities and their rural connections. Although the scope of urban metabolism research does not always consider the rural places from which material and energy flows originated, or that served as sinks for wastes, these hinterland connections are often implied even when they are not explicitly integrated into research, models, and analysis.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.063
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0640.001

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.

Opus teacher head0.012
GPT teacher head0.236
Teacher spread0.224 · 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; both teacher heads agree on what is shown here.

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

Citations0
Published2025
Admission routes1
Has abstractyes

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