Political Parties and Political Systems: The Concept of Linkage Revisited
Bibliographic record
Abstract
Political Parties and Political Systems: The Concept of Linkage Revisited , Andrea Römmele, David M. Farrell, Piero Ignazi, eds., Westport CN: Praeger/Greenwood, 2005, pp. x, 181. This is a book of nine short essays that develop and extend the ideas of linkage theory. The nature of the relationship between citizens and the state, through political parties and other organizations, has been a focus of study in a range of democratic regimes at least since de Tocqueville. Kay Lawson has dedicated a career to the study and classification of linkage relationships and to developing theories about how citizens and subjects are linked to the state. Lawson's best-known works included The Comparative Study of Political Parties (1976), Political Parties and Linkage: A Comparative Perspective (1980), When Parties Fail: Emerging Alternative Organizations (co-edited with Peter H. Merkl, 1988), and How Political Parties Work: Perspectives from Within (1994).. This volume does not claim to be a festschrift but it celebrates, applies and extends her work.
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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 | 0.006 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.012 |
| Science and technology studies | 0.006 | 0.043 |
| Scholarly communication | 0.017 | 0.029 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.006 | 0.007 |
| Insufficient payload (model declined to judge) | 0.009 | 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".