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Record W2968547382 · doi:10.1111/rego.12272

Business conflict and international law: The political economy of copyright in the United States

2019· article· en· W2968547382 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

VenueRegulation & Governance · 2019
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicPolitical Influence and Corporate Strategies
Canadian institutionsUniversité LavalCanadian Institute for International Peace and Security
Fundersnot available
KeywordsPoliticsThe InternetNegotiationIncentiveOrder (exchange)Law and economicsPolitical economyBusinessEconomicsPublic relationsLawPolitical scienceMarket economyFinance

Abstract

fetched live from OpenAlex

Abstract The internet industry has emerged as an important economic and political actor, both within the United States and internationally. Internet companies depend on exceptions from copyright law in order to operate. As a result, internet companies have considerable incentive to try and influence international copyright law. However, the current literature has neglected the role of the internet industry, instead focusing on the influence of copyright owning media companies. This has largely homogenized the concerns of business interests, neglecting the interests of business actors which do not favor stricter copyright protection. By examining business conflict over recent copyright initiatives by the United States, this article criticizes the literature. It illustrates that the internet industry has been able to alter the negotiating preferences of the United States against the wishes of copyright owners. This argues against the homogenization of business interests regarding copyright while illustrating the importance of material over discursive factors in determining political outcomes.

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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.632
Threshold uncertainty score0.248

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 communication0.0000.001
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 head0.022
GPT teacher head0.241
Teacher spread0.219 · 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