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Record W3189160594 · doi:10.5204/ijcjsd.1908

Transnational State-Corporate Symbiosis of Public Security: China’s Exports of Surveillance Technologies

2021· article· en· W3189160594 on OpenAlexaboutno aff
Ausma Bernot

Bibliographic record

VenueInternational Journal for Crime Justice and Social Democracy · 2021
Typearticle
Languageen
FieldEnvironmental Science
TopicWildlife Conservation and Criminology Analyses
Canadian institutionsnot available
FundersGriffith University
KeywordsChinaState (computer science)Corporate governanceBusinessEmerging technologiesInternational tradeEmerging marketsNational securityPolitical scienceFinance

Abstract

fetched live from OpenAlex

Over the last two decades, the emerging Chinese Party-state has used commercial ties with North American and European providers of surveillance technologies to grow national prowess of public security, fostering a transnational state-corporate symbiosis. The exports of surveillance technologies from the Global North to China started in the late 1970s, and now Chinese technology companies are competing with and replacing those suppliers in the globalized neoliberal market. This research explores the two-way dynamic of China’s state and private surveillance capacity underscored by international companies’ profit-seeking behaviors and domestic technological and economic growth. Four case studies of companies from Canada, China, and the US are used to highlight the changing dynamics in the global circulation of surveillance technologies. Particular attention is paid to the cyclical nature of such technologies through which unresolved issues of global governance continue to emerge and, accordingly, support the growth of technology-powered authoritarianism worldwide.

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 score0.088
Threshold uncertainty score0.373

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 communication0.0000.000
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 head0.050
GPT teacher head0.306
Teacher spread0.255 · 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

Citations7
Published2021
Admission routes1
Has abstractyes

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