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Record W2779102116

Technological Fetishism and US Foreign Policy: The Mediating Role of Digital ICTs

2017· article· en· W2779102116 on OpenAlexaff
Edward A. Comor

Bibliographic record

VenueScholarship@Western (Western University) · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicPolitical theory and Gramsci
Canadian institutionsWestern University
Fundersnot available
KeywordsFetishismMarxist philosophyICTSForeign policyThe InternetSociologyPoliticsPolitical scienceInformation and Communications TechnologyPolitical economyLawComputer science
DOInot available

Abstract

fetched live from OpenAlex

This article looks back at an Obama administration foreign policy initiative called Internet freedom and discusses US responses to anti-American extremism involving digital communications technologies. It does this by using Marx’s concept of the fetish to argue that technological fetishism played a constitutive and mediating role in policymaking. Through this analysis – relating international relations with political economy and Marxist theory – the empowering implications of these technologies for American state interests are shown to be also disempowering. Most US officials were likely to be aware that digital communications technologies did not have the inherent powers that their policies implied but, nevertheless, they continued to develop and apply Internet freedom and related policies as if they did. This paradox, it will be underlined, is in keeping with Marx’s analysis of the complex reality whereby the fetish performs a mediating role in institutionalized ways of thinking.

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)0.003
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.007
Threshold uncertainty score0.035

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0050.019
Scholarly communication0.0070.005
Open science0.0000.005
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0040.000

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 head0.089
GPT teacher head0.345
Teacher spread0.256 · 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 designNot applicable
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

Citations13
Published2017
Admission routes1
Has abstractyes

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