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Record W3179968976 · doi:10.4324/9781003134022-13

The contribution of international forums apart from UNESCO in achieving the objectives of the Convention on the Diversity of Cultural Expressions in the digital environment

2021· book-chapter· en· W3179968976 on OpenAlexaff
Clémence Varin

Bibliographic record

Venuenot available
Typebook-chapter
Languageen
FieldSocial Sciences
TopicWorld Trade Organization Law
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsConventionDiversity (politics)Convention on Biological DiversityPolitical scienceCultural diversityPublic relationsComputer scienceGeographyEnvironmental resource managementLawBiodiversityEcologyEnvironmental scienceBiology

Abstract

fetched live from OpenAlex

The UNESCO 2005 Convention on the Protection and Promotion of the Diversity of Cultural Expressions recognizes the dual nature (cultural and economic) of cultural activities, goods, and services, as well as the sovereign rights of states to adopt policies to protect and promote the diversity of cultural expressions on their territory. The challenges posed by digital technologies on the diversity of cultural expressions led to the adoption in 2017 of “Operational Guidelines on the Implementation of the Convention in the Digital Environment”. These guidelines underscore, among others, the importance for parties to promote the objectives and principles of the Convention at the international level when engaging in other forums then UNESCO– as provided for in Article 21 of the Convention– to protect and promote the diversity of cultural expressions in the digital environment. This chapter seeks to demonstrate how international forums apart from UNESCO can contribute to pursuing the Convention’s objectives in the digital environment. At a time when many international forums are attempting to regulate multiple digital phenomena, parties to the Convention must ensure the decisions taken within them do not go against the diversity of cultural expressions, which implies promoting the objectives and principles of the treaty when necessary.

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)0.001
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: none
Teacher disagreement score0.934
Threshold uncertainty score0.417

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.017
GPT teacher head0.236
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

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 designTheoretical or conceptual
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
Published2021
Admission routes1
Has abstractyes

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