Participatory censorship: How online fandom community facilitates authoritarian rule
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.
Bibliographic record
Abstract
Following a burgeoning literature on private actors under digital authoritarianism, this study aims to understand the role played by social media users in sustaining authoritarian rule. It examines a subcultural community—the queer-fantasy community—on Chinese social media to expound how members of this community interpreted China’s censorship policy, interacted based on the interpretation, and participated in censorship. Integrating structural topic modeling and emergent coding, this study finds that a political environment of uncertainty fostered divergent imaginaries about censorship. These imaginaries encouraged participatory censorship within the online community, which strengthened the political control of the Internet in the absence of the state. This study illuminates how participatory censorship works, especially in non-professional and non-politically mobilized online communities. With a focus on social media users, it also offers a lens for future research to compare peer-based surveillance and content moderation in authoritarian and democratic contexts.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.003 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it