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Record W6911342495 · doi:10.5281/zenodo.11389227

INSTAR webinar slides - Shaping International Standards in Advanced ICT Tech Regulation: An Introduction to INSTAR and its Global Impact

2024· article· en· W6911342495 on OpenAlexaboutno aff

Bibliographic record

VenueZenodo (CERN European Organization for Nuclear Research) · 2024
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicDigital Platforms and Economics
Canadian institutionsnot available
FundersEuropean Commission
KeywordsInteroperabilityGeopoliticsLegislationCorporate governanceGlobal governanceBest practiceInformation and Communications TechnologyGood governanceEuropean union

Abstract

fetched live from OpenAlex

In the EU policy context, standardisation plays a pivotal role in shaping regulations that safeguard end users while fostering market-based competition and interoperability of complementary products and services. The EU Standardisation Strategy underscores the necessity for the EU to assert a leadership position in global standardisation processes. This strategic approach not only enhances international cooperation but also aligns with broader EU objectives such as protecting EU strategic interests and promoting EU rules as global standards. An essential element of the strategy is "multilateral engagement" through Europe’s Digital Partnerships and the EU-US Trade and Technology Council (TTC), which involves collaborating with international partners to forge a consensus on international standards. This cooperation is crucial for maintaining economic security and reinforcing mutual resilience, particularly in a complex geopolitical environment. Thus, the broader framework of multilateral engagement is exactly where INSTAR plays a crucial role. INSTAR is an EU-funded project that aims to support the implementation of Europe’s Digital Partnerships and the EU-US TTC by working together with relevant entities from Australia, Canada, Japan, Singapore, South Korea, Taiwan and the USA to drive international common standards for AI, Cybersecurity, Digital ID, Quantum Technologies, IoT, 5G, 6G and Data Technologies. To do this, INSTAR will establish expert Task Forces to analyse and identify European standardisation priorities and legislation in these areas, share best practices and provide recommendations to be taken in to foster greater international cooperation and enhance EU's strategic positioning in the global tech governance landscape. The webinar featured Emilio Davila Gonzalez (EC DG CNECT Policy Officer, Head of ICT Standardisation Sector) who highlighted the strategic role that INSTAR and its Task Forces will play in sharing European best practices and priorities in order to facilitate international dialogue on standardisation. As the INSTAR project currently sets up the Task Forces, the webinar was an opportunity to target and attract potential members who are essential in shaping the future of standardisation in these technology fields.

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 categoriesScholarly communication, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.923
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0040.006
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.001

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 head0.028
GPT teacher head0.267
Teacher spread0.239 · 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.

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
Published2024
Admission routes1
Has abstractyes

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