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Citying in the Anthropocene

2015· article· en· W2756438512 on OpenAlexaff
Michael Jemtrud, Keith G. Ragsdale

Bibliographic record

VenueArchitecture_MPS · 2015
Typearticle
Languageen
FieldArts and Humanities
TopicEcocriticism and Environmental Literature
Canadian institutionsMcGill University
Fundersnot available
KeywordsAnthropoceneProsperityRealmHumanityEnvironmental ethicsSociologyPoliticsPaceAestheticsSocial sciencePolitical scienceGeographyLaw

Abstract

fetched live from OpenAlex

Historically, cities have been the repository and medium for our collective works, aspirations, and celebrations, driven by the promise of prosperity, wellbeing, and societal accord. Contemporary cities are technologically mediated in a manner that is reconfiguring the spatial and temporal conditions of the urban realm at an unprecedented scale and pace. We are experiencing a substantial transmutation of the material, utilitarian, everyday, spectacular, and symbolic reality of the urban, and with it, our capacity to be urbane, together. Although the design, construction, and operation of cities is seen as chiefly a practical and technical challenge, the “how” must be guided by questions of a fundamental, axiological nature – that is to say, questions concerning the values, ethics, qualities, political and aesthetic experience of urban life. Such qualitative values are most potently expressed in the artefacts and events of a meaningful and productive cultural life. Understanding the relationship between variously formal and informal modes of urban collectivity – referred to in this paper as citying – and the formal practices of city-making as a sophisticated cultural and technical enterprise motivates this inquiry. Furthermore, it will be argued here that such questions concerning culturally defined notions of values are inseparable from our ever-present awareness of humanity’s role in whole-scale environmental degradation otherwise known as the era of the Anthropocene. Thus, a triad is formed – culture–technology–environment – that fundamentally defines the way in which we make and inhabit contemporary cities.

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 imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.013
Threshold uncertainty score0.046

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0130.034
Scholarly communication0.0110.008
Open science0.0010.011
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0100.001

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 head0.056
GPT teacher head0.227
Teacher spread0.172 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
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

Citations0
Published2015
Admission routes1
Has abstractyes

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