The Formation of National Party Systems: Federalism and Party Competition in Canada, Great Britain, India and the United States
Bibliographic record
Abstract
The Formation of National Party Systems: Federalism and Party Competition in Canada, Great Britain, India and the United States. By Pradeep K. Chhibber and Ken Kollman. Princeton: Princeton University Press. 2004. 272p. $50.00 cloth, $24.95 paper. The question of the role institutions play in party aggregation has tended to be dominated by discussions of the role and effects of different electoral systems. In a refreshing change from this preoccupation with electoral systems, Pradeep Chhibber and Ken Kollman turn our attention to the impact of federalism, or, more appropriately, the degree of centralization or devolution of power in governmental systems, on the fragmentation of party systems. Their focus is dynamic: They are interested in the formation of national party systems and in how party systems change over time with respect to their extent of nationalization and in relation to the migration of political authority to the center or from the center to states, provinces, or regions. Highly nationalized party systems are ones in which parties receive similar vote shares across different levels of vote aggregation: district, regional, and national. Conversely, in weakly nationalized party systems, parties are differentially competitive across levels.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.012 |
| Science and technology studies | 0.009 | 0.010 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 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".