Corruption and Partisanship: Rousseau, Ferguson and Two Competing Models of Republican Revival
Bibliographic record
Abstract
Abstract Partisanship inspires a degree of ambivalence. There is a widespread tendency—which has a long history in republican political thought—to decry division and partisanship as corrupting, undermining individual judgment, and promoting clientelism, dependencies and loyalties antithetical to the common good. Yet there is an equally widespread intuition that excessive unity is corrupting, undermining the vigour of civic life. Contemporary political theory remains divided on the normative implications of division and unity—witness the battles between agonistic and consensus-oriented schools of democratic theory. In this article I examine the thought of two eighteenth-century writers who, while often treated as contributing to a common intellectual project of reinvigorating classical civic virtue, took opposite positions on the desirability of division. Jean-Jacques Rousseau and Adam Ferguson offered competing accounts of what corrupts civic virtue, one decrying party divisions and the other lauding them. The article examines the underlying philosophical presuppositions of Rousseau and Ferguson's competing claims and suggests, ultimately, that both positions suffer from neglecting to attend to an important distinction between salutary and harmful divisions.
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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 | 0.008 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.005 | 0.030 |
| Scholarly communication | 0.008 | 0.005 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".