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Record W343436119 · doi:10.15173/mjc.v2i0.227

Technology-centred Discourses in European Audiovisual Policy: Will Euro-Techno out-Fox the US Assembly Line?

2005· article· en· W343436119 on OpenAlexaffvenue
Carmen Amelia. Gayoso

Bibliographic record

VenueThe McMaster Journal of Communication · 2005
Typearticle
Languageen
FieldSocial Sciences
TopicEuropean Union Policy and Governance
Canadian institutionsMcMaster University
Fundersnot available
KeywordsLine (geometry)Political scienceMedia studiesSociology

Abstract

fetched live from OpenAlex

This paper outlines the region-building initiatives of European audiovisual policy that are justified by a technology-centred discourse. While highlighting technology as a central and powerful theme in the European policy discourse, this paper begins to challenge the discourse’s depiction of reality. Specifically, the existing audiovisual environment suggests that notwithstanding Europeanization rhetoric in cultural policy decisions, there is a de facto Americanization of audiovisual space. Because of the apparent failure of the European Union to establish a unified competitive market, this paper analyzes the relationship between three variables competing in cultural policymaking. The first section lays out policy discourses characterized by European identity-formation. The second section describes the reality of cultural patterns in the EU that are characterized by diversity and audience fragmentation. The third section explains the reality of audiovisual space that is characterized by American products. A discussion follows of the restrictive effects that such policy discourse has on future policymaking decisions in the EU, bringing to question the success of any new policy orientation that is based around technology in both harmonizing European broadcasting policy and in rivaling its American competitor.

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)0.002
metaresearch head score (Gemma)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.955
Threshold uncertainty score0.554

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0000.001
Open science0.0030.000
Research integrity0.0000.001
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 head0.036
GPT teacher head0.331
Teacher spread0.295 · 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 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

Citations0
Published2005
Admission routes2
Has abstractyes

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