How autocracy shapes the social sciences
Are the contents and conclusions of the social sciences different in autocracies and democracies?
AutoKnow asks whether science is affected by authoritarian government, and if so, how. The project develops new theories of science under authoritarian rule and tests these with large-scale bibliometric data, surveys, case studies, and computational text analyses of what scientists actually publish.
The puzzle
The growth of scientific knowledge is one of the towering achievements of humankind, yet we still understand little about what makes some societies more fertile for science than others. A long tradition holds that science requires protected freedom of expression and open inquiry. At the same time, authoritarian regimes such as China, Russia, and Saudi Arabia have massively increased their investment in science, and the international scientific frontier is increasingly traversed by countries with unfree elections, weak civil liberties, and limited academic freedom.
Authoritarian rule is not confined to autocracies. Authoritarian leaders and movements have become a major political force inside democracies, where they attack universities, scientists, and scientific institutions. Understanding how authoritarian rule affects science is therefore vital to the future of scientific progress itself, and to the challenges that depend on it, from global health and climate change to governance and AI.
AutoKnow answers this science–authoritarianism puzzle by building the first comprehensive social-scientific account of how authoritarian regimes, and authoritarian leaders in backsliding democracies, constrain scientists and shape the knowledge they produce.
Beyond counting papers
Conventional bibliometrics count publications and citations. AutoKnow starts there, but its core is a set of deeper, content-based dimensions of scientific output, measured with large language models and computational text analysis across the period 1950–2025.
Publication counts and citations across and within disciplines, the workhorse metrics of country-level scientific performance.
Whether published work disrupts established knowledge, contributes novel ideas, and takes intellectual risks.
Whether scholarship on the social world tilts in favour of, or against, governments, regimes, and political authority.
Conspicuous absences: topics, concepts, and findings that should appear in a literature but do not.
Research questions
Approach
Millions of peer-reviewed articles from the Web of Science and OpenAlex, matched to regime data from V-Dem, from 1950 to the present.
A new dataset of attacks on scientists, universities, and scientific institutions by authoritarian regimes and leaders.
Original survey data on scientific norms, self-censorship, and how researchers adapt to political pressure.
LLM-based classification and multi-agent analysis pipelines that read abstracts across languages and measure framing, sensitivity, and bias.
Research in progress
A growing set of papers is currently in production, alongside a planned monograph.
Are the contents and conclusions of the social sciences different in autocracies and democracies?
How do autocratic regimes shape what scientists write?
Does authoritarian rule shape what historians write about their own nation's history?
What did four decades of authoritarian rule do to social science in East Germany?
How has autocratic consolidation in Turkey changed what academics study and how they write?
Does the credibility of scientists depend on their politics, and on the regime they work under?
What are the costs and benefits, for democracies and autocracies, of aligning AI models with the regime?
Where does critical social science come from, and did the student protest movements of the 1960s and 1970s leave a lasting imprint on it?
Can what institutions publish predict which of them come under academic-freedom attacks?
How can the evidence for a "grand theory" with many implications be weighed systematically?
Of the many plausible theories of how autocracy shapes science, how do we decide which ones to test?
People
AutoKnow is led by Tore Wig, Professor of Political Science at the University of Oslo, together with associated researchers at Oslo and Stavanger and co-authors in Berlin, Dublin, Konstanz, and Santiago. The project is recruiting two postdoctoral fellows and two PhD fellows.
Updates
Project website launched with an overview of the growing set of papers currently in development.