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Record W7070677564

Reclaiming digital sovereignty: A roadmap to build a digital stack for people and the planet

2024· article· en· W7070677564 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.

fundA Canadian funder is recorded on the work.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueUCL Discovery (University College London) · 2024
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMachine Learning in Bioinformatics
Canadian institutionsnot available
FundersUniversidade Federal do ParanáInstituto Tecnológico y de Estudios Superiores de MonterreyUniversidad de CórdobaUniversità degli Studi di SienaConsejo Nacional de Investigaciones Científicas y TécnicasUniversidade Federal do Rio de JaneiroUniversidade Federal de Minas GeraisUniversiteit van AmsterdamLondon School of Economics and Political ScienceUniversity College LondonUniversity of TorontoUniversitat Pompeu FabraVrije Universiteit AmsterdamUniversiteit UtrechtPolitecnico di TorinoUniversidad Nacional de Córdoba
KeywordsSovereigntyAgency (philosophy)Civil societyGovernment (linguistics)The InternetState (computer science)MisappropriationDemocracy
DOInot available

Abstract

fetched live from OpenAlex

This policy paper outlines a progressive reform agenda to enhance digital sovereignty for people and the planet with the following 4 key proposals: 1. Offer a democratic, public-led digital stack that shall include: 1) Digital infrastructure as a service (for training, processing and developing digital solutions) provided by non-profit and democratic international consortia; 2) universal platforms, such as search engines and foundation AI models, that should be a commons governed by new public institutions with state and civil society representation; and 3) a public marketplace where companies can offer their computing services without lock-ins. To assure demand, states shall procure from this marketplace and end contracts with Big Tech. 2. Craft a research agenda focused on digital developments that could solve collective problems and enhance human capacities and that consider the ethical, economic, ecological, and political impacts of technology, including of AI applications. For this end, public knowledge networks led by a new public international research agency (or agencies) could counterbalance the concentration of private and closed science. 3. Ground digital sovereignty in an ecological internationalism an antidote to individual government surveillance and power abuses that also minimises the resources needed to build a democratic, public digital stack. 4. Establish strict mechanisms to dismantle state surveillance or misappropriation of collective solutions by specific governments. Multilateral agreements on principles and rules for the internet are indispensable safeguards for building autonomous and democratically governed institutions and solutions. To complement and facilitate all the above, the authors further lay out a strategy on retrofit markets’ authorities for the digital age and implement measures to properly regulate and tax revenues and data and knowledge capture of dominant technology companies. The new policy framework outlined in the paper also aims at protecting labour and enhancing its creative autonomy while contributing to the reinforcement of human and civil rights. One aspect could be a safety net in which states offer training and employment for the development and operation of the public-led digital stack.

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: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.499
Threshold uncertainty score0.642

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 communication0.0000.000
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 head0.004
GPT teacher head0.197
Teacher spread0.193 · 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