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Record W4306698178 · doi:10.1177/01634437221128937

On super apps and app stores: digital media logics in China’s app economy

2022· article· en· W4306698178 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

VenueMedia Culture & Society · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicDigital Economy and Work Transformation
Canadian institutionsCanada Research ChairsUniversity of Toronto
Fundersnot available
KeywordsOperationalizationChinaApp storeDominance (genetics)FinancializationBusinessEconomyPolitical scienceComputer scienceEconomicsWorld Wide WebFinance

Abstract

fetched live from OpenAlex

Aiming to enrich the conceptual vocabulary of platform and app studies, this article provides a critical political economic perspective on the media industry to understand how platform power is operationalized in the app economy. Using the China-based tech conglomerate Tencent as a case study, four mechanisms are discussed: conglomeration, financialization, platformization, and infrastructuralization. These mechanisms show how Tencent leveraged both a conglomerated corporate structure and access to finance capital. This was combined with the infrastructuralization of the MyApp app store and the WeChat platform by providing vertically integrated app development and distribution services, which are nested in Tencent’s holdings and investments. Taking Tencent as the starting point for theory building, this article attempts to “provincialize” US-based platform companies by charting Tencent’s corporate evolution and its path to mobile dominance.

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: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.802
Threshold uncertainty score0.545

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 studies0.0010.000
Scholarly communication0.0000.001
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 head0.009
GPT teacher head0.219
Teacher spread0.210 · 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