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Record W4288595738 · doi:10.31235/osf.io/wkqy2

Social justice in the digital age: re-thinking the smart city with Nancy Fraser. UCCities Working Paper # 1

2019· preprint· en· W4288595738 on OpenAlex

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

Venuenot available
Typepreprint
Languageen
FieldEngineering
TopicSmart Cities and Technologies
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsTransformative learningSmart cityEconomic JusticeSociologySocial justiceRepresentation (politics)Redistribution (election)UrbanismIntervention (counseling)Environmental justiceConceptual frameworkEpistemologyPolitical scienceLaw and economicsSocial scienceArchitectureLawInternet of ThingsGeographyComputer scienceComputer securityPoliticsPsychology

Abstract

fetched live from OpenAlex

While many urban scholars acknowledge the importance of justice and participation for emerging smart city initiatives, these dimensions remain inadequately addressed in critical literature. To strengthen the smart city critique, in this conceptual intervention we employ the theory of justice developed by philosopher Nancy Fraser, organized along the domains of redistribution, recognition, and representation. Using Fraser’s tripartite framework of justice, we reformulate and expand the existing critiques of the smart city. Moreover, drawing on her notion of transformative approaches, we argue for shifting the discussion away from the smart city, even an alternative one, towards the just city and a just urbanism in the digital age.

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.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.515
Threshold uncertainty score0.841

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 studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.002
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 head0.026
GPT teacher head0.226
Teacher spread0.200 · 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

Quick stats

Citations8
Published2019
Admission routes1
Has abstractyes

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