The other civil society: digital media and grassroots illiberalism in Bulgaria
Bibliographic record
Abstract
The goal of the small-scale exploratory study presented in this article is to examine the digital mediation of grassroots processes unfolding within Bulgarian civil society that contribute to the strengthening of the social base and cultural influence of illiberal ideologies and citizen organisations. While ample attention has been paid to the utility of digital media in progressive movements and mobilizations, much less is known about their use by illiberal activists. The methodology comprises two case studies, each focused on a different collective actor that espouses ‘illiberal’, nationalist and intolerant views. Using the concept of ‘uncivil society’ proposed by Kopecký and Mudde ([2003]. Uncivil Society: Contentious Politics in Post-Communist Europe, London: Routledge), the paper approaches the analysis of the positions and activities of these organisations from two angles: (1) the way in which these actors appropriate discourses of ‘patriotism’ and ‘civil society’ and (2) the way they employ digital media to construct collective identities and build up support. The analysis casts light on the role digital media play – at the hands of such actors – in the rise of illiberal and ‘uncivil’ advocacy that could lead to the conquest of civil society by illiberalism and a continuing political backslide of liberal democracy.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.007 | 0.014 |
| Scholarly communication | 0.009 | 0.004 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".