Comparing Federations: Lessons from Comparing Canada and the United States
Bibliographic record
Abstract
Unlike the usual overview of the state of American Federalism, this special issue compares the state of federalism in the United States and Canada. The articles are drawn from papers delivered at a September 2009 conference on the U.S. and Canadian federalism cosponsored by Publius and the Federalism and Intergovernmental Relations Section of the American Political Science Association.1 In this overview, we briefly highlight interesting findings and trends reported in the articles and outline some difficulties they reveal regarding comparative federalism work. There is little doubt that comparative research is challenging, even when it involves two much-studied federal systems such as Canada and the United States. Comparative data are often difficult to obtain and conclusions—including those outlined in this issue—are at best conditional, depending on each federation’s unique amalgam of properties and contexts; or what Katherine Harrison terms “it depends.”2 In their contribution, Beryl Radin and Richard Simeon warn that systematic, comparative federalism research raises complex issues: such as whether comparing Canadian and the U.S. Federalism involves a similar- or different-system approach. Their framework focuses on each federation’s “big ideas,” institutions, and historical legacies; an approach those who think federal societies shape the development of federally governed countries will consider wrongheaded. Michael Hail and Stephen Lange’s article comparing influences on the foundings of the two federations identifies the “big ideas” they believe shaped the U.S. and Canadian federations. They theorize that both federations share the same underlying political philosophy despite different historical legacies and societal types.
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 | 0.014 | 0.057 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.017 | 0.036 |
| Science and technology studies | 0.026 | 0.011 |
| Scholarly communication | 0.015 | 0.009 |
| Open science | 0.004 | 0.007 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.005 | 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".