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Record W3032767697 · doi:10.1177/0042098020919086

An urban political ecology for a world of cities

2020· article· en· W3032767697 on OpenAlexaff
Roger Keil

Bibliographic record

VenueUrban Studies · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicEnvironmental Justice and Health Disparities
Canadian institutionsYork University
Fundersnot available
KeywordsPoliticsRhetorical questionUrbanizationEnvironmental ethicsSociologyPolitical ecologyField (mathematics)Work (physics)Political scienceEngineering ethicsEcologySocial scienceEngineeringLaw

Abstract

fetched live from OpenAlex

The critical considerations in this commentary have been stimulated by the articles joined together in this inspiring collection. Specifically, this commentary reflects on how one might imagine an urban political ecology for the age of planetary urbanisation. While the editors of and contributors to this special issue have done an admirable job of providing intellectual coherence to this project, there remains work to do, especially on the conceptual and theoretical front. The conveners of this symposium lay out an ambitious agenda for the papers in this issue and ultimately for the field: They ask: ‘why does everyone think cities can save the planet?’. It is part real inquiry, part rhetorical question. These questions also provide the entry point into a coherent and serious theoretical project that lies at the bottom of the assembled papers here and is elegantly laid out by the special issue editors in their introduction. This commentary takes up the challenges posed by the theoretical and empirical projects discussed in this issue and discusses them in light of past advances in thinking across the city–nature divide, technological politics and the changing spaces and times of current urbanisation.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.689
Threshold uncertainty score0.322

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.099
GPT teacher head0.390
Teacher spread0.292 · 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; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

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

Citations27
Published2020
Admission routes1
Has abstractyes

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