Adapting Federalism: Indigenous Peoples and Multilevel Governance in Canada and the United States
Bibliographic record
Abstract
A significant body of literature has recently emerged on federalism in culturally and ethnically diverse societies. In addition to theory driven work on institutional design in multinational federations, recent empirical analyses have focused on the impact of ethno-linguistic diversity on the working and evolution of federations. These analyses point to the relative plasticity of federal systems in adapting to the social fabric of a polity, thus ensuring both the stability of the federal union and its capacity to adapt to the ongoing tensions created by ethnic and linguistic divisions. They also provide an important insight into how multinational federations evolve by inviting us to shift our focus away from the “high politics” of constitutional design and pay more attention to the policy process as a space where institutional patterns are redefined and adapted to reflect ethno-linguistic divides in federations. Like most of the literature on federalism in multinational societies however, authors working on policy-level change assume national minorities have some degree of control over at least one of the constituent units of the federation. What happens in cases where territorially defined minorities do not control the institutions of one of the federated units? Indigenous peoples in Canada and the United States are a classic case of small, territorially defined, minorities who were excluded from the original federal compact of both countries. Can federalism adapt to Indigenous claims? If so, how? Building on theories of path dependent institutional change, I suggest federalism in Canada and the United States has evolved in light of Indigenous autonomy demands. This evolution, however, is largely taking place at the margin of the federal system, through processes of governance that are layered over, and often in tension with, the formal division of powers and intergovernmental regimes that characterize Canadian and American federalism.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.026 | 0.014 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".