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Record W4413859142 · doi:10.1080/02723638.2025.2551135

The citizen and the smart city: a global comparison of institutional logics

2025· article· en· W4413859142 on OpenAlexafffund
Tim Bunnell, Zachary Spicer, Byron Miller, Teresa Abbruzzese, Paolo Cardullo, I-Chun Catherine Chang, Greig Charnock, Ming-Kuang Chung, Kwon Heo, Sue-Ching Jou, Andrew Karvonen, Olga Kordas, Lily Kong, Ramón Ribera-Fumaz, HaeRan Shin, Orlando Woods

Bibliographic record

VenueUrban Geography · 2025
Typearticle
Languageen
FieldEngineering
TopicSmart Cities and Technologies
Canadian institutionsUniversity of CalgaryYork University
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsCitizen scienceSmart citySociologyPolitical sciencePublic administrationGeographyComputer scienceInternet privacyInternet of ThingsBiology

Abstract

fetched live from OpenAlex

Critical urbanists’ placement of smart city initiatives in Western Europe or North America mostly on “low” rungs of participatory ladders or scaffolds does not mean that smart urban development connotes democracy-eroding neoliberalization everywhere. This article offers a more globally variegated and dynamic understanding of the relationship between citizens and smart cities. We apply an institutional logics frame to the citizen-smart city nexus in seven cities spanning three world regions, in each case considering the interplay of citizen-centric logics with techno-innovation-oriented and bureaucratic/managerial logics. Appreciation of contextually specific institutional orders helps to explain why similar initiatives and intentions yield different outcomes across time and space, but the interplay of competing logics also enables a reworking of prevailing orders and possibilities for change. Bringing multiple cases and associated dynamics into comparative conversation reveals similarities and differences that would not have been expected from a priori classifications based on geographical region or mode of governance, affording cross-case conceptualization of civil servant “proxy citizenship” and “palimpsests” of social scripts. The article provides empirical, methodological and conceptual resources not only for understanding how prevailing institutional logics variously enable or foreclose citizen action in smart city development, but also for building contextually-attuned propositional agendas for change.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.307
Threshold uncertainty score0.286

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 head0.008
GPT teacher head0.216
Teacher spread0.208 · 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 designObservational
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

Citations2
Published2025
Admission routes2
Has abstractyes

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