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Record W4406252029 · doi:10.1002/poi3.434

Resisting and Claiming Digital Sovereignty: The Cases of Civil Society and Indigenous Groups

2024· article· en· W4406252029 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

VenuePolicy & Internet · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicCybersecurity and Cyber Warfare Studies
Canadian institutionsUniversité LavalUniversité de Montréal
Fundersnot available
KeywordsSovereigntyIndigenousCivil societyPolitical scienceDigital societyLawSociologyMedia studiesPolitics

Abstract

fetched live from OpenAlex

ABSTRACT In this contribution to “Unthinking digital sovereignty,” we review some discourses and practical proposals that resist or challenge the digital sovereignty of “established states.” Our focus centers on two distinct sociopolitical groups engaged in such practices. The first group we highlight is what we call “civil society,” which is composed of nongovernmental, nonprofit organizations, and collectives, often inspired by anti‐capitalist, autonomist, and anarchist ideas, actively involved in building self‐managed digital infrastructures based on free and open‐source software and hardware. The second group consists of Indigenous peoples and organizations that have developed a robust discourse on “data sovereignty,” referring to the sovereignty of knowledge and data related to them. Finally, we discuss four contributions from our review that help “unthink” digital sovereignty: (1) the values of autonomy and self‐determination, which are quite important beyond state‐centric models; (2) the cultural dimensions of digital sovereignty; (3) the question of “openness,” which emerges as a point of tension between the perspectives; and finally; (4) the relevance of the concept of sovereignty itself in addressing these issues.

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: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.333
Threshold uncertainty score0.986

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 studies0.0000.001
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 head0.025
GPT teacher head0.307
Teacher spread0.282 · 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