Enemies, Adversaries & Unlikely Allies: Reimagining Agonal Democratic Theory Through a Classical Sociological Lens
Bibliographic record
Abstract
Set against the backdrop of increasingly polarized and dysfunctional political discourse within western democratic nations, this dissertation aims to consider the ways in which critical sociology can contribute to, and potentially expand, emergent accounts of an alternative radical democratic politics premised on productive contest. While the mainstream of democratic theory remains dominated by notions of deliberation, compromise, and consensus; a challenge has emerged out of a small but important paradigm of social and political theory - one that conceptually re-prioritized the political ideal of agon. Rejecting notions of post-political compromise or consensus, contemporary scholars of agonal democracy propose perpetually open contest, legitimated struggles, and irresolvable tensions as the proper and desirable content of the political. Yet as richly as these varying accounts have mapped the political character of such agonal principles, very little attention has been paid to their implicit or explicit social dimensions. Through the creative adaptation of certain sociological perspectives of Max Weber, Ferdinand Tnnies, Georg Simmel, and Jrgen Habermas; this project attempts to rethink the social in the context of radical agonistic democracy. Taking up the work of Chantal Mouffe as an exemplar of this agonal paradigm, this project challenges the often-shallow accounts of the social, ultimately suggesting an alternative, though complimentary, theoretical vocabulary through which to explore the important, but consistently underexplored, social dimensions of a (re)turn to the political ideal of agon.
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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 | 0.013 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.001 |
| Science and technology studies | 0.013 | 0.081 |
| Scholarly communication | 0.016 | 0.018 |
| Open science | 0.002 | 0.011 |
| Research integrity | 0.003 | 0.008 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".