Handbook of federal countries, 2002
Bibliographic record
Abstract
For more than two centuries federalism has provided an example of how people can live together even as they maintain their diversity. The Handbook of Federal Countries, 2005 continues the tradition started by the 2002 edition, updating and building on the work of Ronald Watts and Daniel Elazar in providing a comparative examination of countries with federal tendencies. Unique in its timely scope and depth, this volume begins with a foreword by Forum President Bob Rae that reflects on the importance of the federal idea in the contemporary world and provides an excellent introduction to federalism. New comparative chapters examine the recent draft constitutional treaty in Europe and the possibility of federalism being adopted in two countries with longstanding violent conflicts - Sri Lanka and Sudan. As a project of the Forum of Federations, an international network seeking to strengthen democratic governance through federal values, practices, and principles, the 2005 handbook is an essential sourcebook of information with maps and statistical tables in each chapter. The international authors examine a wide range of themes including the development of federalism in the country, the constitutional provisions relating to federalism, and the country's current political dynamics. The authors also include sources readers can consult for more information. Contributors include Dirk Anthony Ballendorf (University of Guam), Kaiser Bengali (Social Policy and Development Centre, Pakistan), Allan Brewer-Carias (Columbia University), David Cameron (University of Toronto),Valeriano Mendes Ferreira Costa (Sao Paulo - Brasil), Mihailo Crnobrnja (special advisor, Government of Serbia), Rohan Edrisinha (University of Colombo), Ann Griffiths (Dalhousie University), Siobhan Harty (Department of Social Development, Ottawa), Rudolf Hrbek (University of Tuebingen, Germany), Paul King (Management Systems International, Nigeria), Andre Lecours (Concordia University), George Mathew (Institute for Social Sciences, India), Gordon Means (emeritus, McMaster University), Yemile Mizrahi (Washington, DC), Viviana Patroni (York University), Tom Patz (Gesellschaft fur technische Zusammenarbeit), Cesare Pinelli (University of Macerata), Cheryl Saunders (University of Melbourne), Sanford Schram (Bryn Mawr College), Lee Seymour (Northwestern University), Julie Simmons (University of Guelph), Thomas Stauffer (University of Fribourg), Roland Sturm (University of Erlangen-Nurnberg), Janis van der Westhuizen (Stellenbosch University), Gary Wilson (University of Northern British Columbia), and Marie-Joelle Zahar (Universite de Montreal).
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.005 | 0.009 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.197 | 0.126 |
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".