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Platforms and Global Democracies

2025· reference-entry· en· W4411356425 on OpenAlex
Daniel Kreiss, Lorcan Neill

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.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
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

VenueOxford Research Encyclopedia of Communication · 2025
Typereference-entry
Languageen
FieldSocial Sciences
TopicSocial Media and Politics
Canadian institutionsnot available
Fundersnot available
KeywordsComputer sciencePolitical science

Abstract

fetched live from OpenAlex

Abstract Since approximately 2003−2004, social media and technology platforms have become central infrastructures for political processes around the world. In many countries, technology and social media platforms such as Facebook, Google, Instagram, YouTube, and TikTok play a central role in public debate, social movements, governmental communication, public diplomacy, terrorism, war, campaigns, elections, governance, and policymaking, in addition to many other domains. As such, how these companies are governed, monetize content and users, set policies, and design technologies has outsized implications for global and national public spheres and political processes, including electoral institutions. These platforms are embedded in political, social, and economic systems that influence how they are governed and used—and which they in turn shape. Platforms have a complicated past when it comes to regulating political content. The role of mis/disinformation on social media platforms in the wake of the international Cambridge Analytica scandals and the rise of populist, authoritarian, or anti-democratic leaders and parties led to new global calls for increased regulation of these technologies once thought to be tools of liberation and democracy. Between 2016 and 2020, platforms responded by instituting a number of different content-moderation policies, strategies, and partnerships to address issues surrounding their role in democratic politics. Platforms took more seriously the propagation of conspiratorial content, the correction of misleading information, and the policing of content that undermined electoral processes. Since that time, platforms have generally rolled back trust and safety efforts, with stated justifications of freedom of expression. This article provides an overview of what is known about social media platforms and democratic processes, including their social and psychological effects. It analyzes platform policies belonging to Meta (Facebook, Instagram, and WhatsApp), X, YouTube, and TikTok regarding political and election-related content in six countries (Australia, Canada, India, Mexico, the United Kingdom, and the United States) as well as the European Union—all places holding elections in 2024 or 2025. The article focuses on the civic integrity, artificial intelligence, fact-checking, and political advertising policies of these platforms, given their importance to global politics and elections.

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)0.002
metaresearch head score (Gemma)0.003
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: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.865
Threshold uncertainty score0.941

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.002
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0010.001
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 head0.076
GPT teacher head0.424
Teacher spread0.348 · 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