Book review: Federal Dynamics: Continuity, Change and the Varieties of Federalism
Bibliographic record
Abstract
Federal systems are praised for creating political stability, but they are also blamed for causing rigidity. They are said to balance powers, but apparently they are also threatened by instability due to drifts in power. Federalism should support democratization, but it can also constrain the power of the demos and strengthen the executive. In short, there is widespread agreement that federal systems are dynamic. The forces, mechanisms and consequences of federal dynamics, however, are not sufficiently understood so far. This book brings together leading experts in the field of comparative federalism to highlight how the interplay of continuity and change systematically generates and reinforces varieties of federalism and varieties of federal dynamics. Federal Dynamics: Continuity, Change and Varieties of Federalism investigates mechanisms and resulting patterns of federal development. It offers new analytical concepts and discusses different theoretical propositions to systematically compare convergent and divergent trends in federal systems. Acknowledging the theoretical pluralism that dominates the field, the book is organized around four sections: Models, Varieties and Dimensions of Federalism; Timing, Sequencing and Historical Evolution; Social Change and Political Structuring; and Actors, Institutions and Internal Dynamics. The contributions to this volume are variously concerned with three guiding questions: What changes within federal systems, how and why? The focus provided by these three guiding questions allows for a dialogue between strands of the literature that have not talked to each other in a sufficient manner. In this way, the book makes a significant contribution to the growing literature on continuity and change in federal systems. Ultimately, it represents a substantive effort in advancing research on comparative federalism.
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.
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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.042 | 0.016 |
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".