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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 OpenAlexaff
Marit Rosol, Gwendolyn Blue, Victoria Fast

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.

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)0.005
metaresearch head score (Gemma)0.007
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: Other · Consensus signal: none
Teacher disagreement score0.011
Threshold uncertainty score0.058

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.007
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0100.021
Scholarly communication0.0110.018
Open science0.0010.007
Research integrity0.0060.007
Insufficient payload (model declined to judge)0.0080.001

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 head0.026
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

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
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

Citations8
Published2019
Admission routes1
Has abstractyes

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