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Record W4410311984 · doi:10.1177/20539517251338776

Localized processes of platformization: The example of Surabaya

2025· article· en· W4410311984 on OpenAlex
Alessandra Renzi, Janna Frenzel

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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueBig Data & Society · 2025
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicSharing Economy and Platforms
Canadian institutionsConcordia University
FundersConcordia University
KeywordsComputer scienceSociology

Abstract

fetched live from OpenAlex

This article analyzes how universalist paradigms for platform urbanism are being adapted, modulated, and subverted through an evolving platform ecosystem that is specific to the city of Surabaya, Indonesia's second largest city. We examine how processes of urban planning and city management are platformized, how specific groups of professionals and residents act as intermediaries between infrastructure and users and thereby facilitate the platformization process, and how these local iterations of platforms are informed by place-specific colonial and national history. By describing and tracing the genealogy of Surabaya's platform ecosystem, we demonstrate the specific ways in which it rationalizes city governance, shapes discourses on participatory citizenship and spatial planning, and redefine what counts as city infrastructure, innovation, and urban life in general. We argue that the modulation, adaptation, and resistance to platformization can only be understood by paying attention to the singularity of the milieu and tracing how visions of modernity and its sociotechnical assemblages are composed anew every time platform frameworks, tech tools, and discourses hit the ground.

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: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.448
Threshold uncertainty score0.267

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.115
GPT teacher head0.262
Teacher spread0.147 · 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