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Record W2610468569 · doi:10.1177/136787790364004

Beating them at their Own Game

2003· article· en· W2610468569 on OpenAlexaff
Kirsty Best

Bibliographic record

VenueInternational Journal of Cultural Studies · 2003
Typearticle
Languageen
FieldSocial Sciences
TopicDigital Economy and Work Transformation
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsCommodificationPoliticsSociologyDemocracyValue (mathematics)Media studiesPublic relationsPolitical economyAestheticsPolitical scienceLawEconomicsComputer scienceMarket economy

Abstract

fetched live from OpenAlex

This article interrogates the validity of claims that the open software movement provides a substantial alternative to intellectual property and a challenge to the encroaching commodification of digital space. The open software movement is participating in ongoing language wars of the new communication technologies; it is attempting to redefine the social and economic value of information and computer networking, and as such does present a challenge to digital commodification. However, this challenge is not mounted through traditional and public-oriented modes of cultural politics but instead through personal and bodily re-imaginings and a direct engagement with the new technologies. Indeed, similarities exist between discourses of the open software movement and capitalist discourses of flexible work and the reinvention of labour as temporary, transient and empowered. In sum, the open software movement can be considered to enable forms of visceral democracy, and its political potential is capacitated but also restricted by this form of cultural politics.

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)0.009
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 score0.067
Threshold uncertainty score0.224

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.009
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0070.006
Scholarly communication0.0100.008
Open science0.0020.009
Research integrity0.0020.005
Insufficient payload (model declined to judge)0.0670.025

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 head0.070
GPT teacher head0.340
Teacher spread0.270 · 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

Citations14
Published2003
Admission routes1
Has abstractyes

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