Federal Constitutions, Global Governance, and the Role of Forests in Regulating Climate Change
Bibliographic record
Abstract
Federal systems of government present more difficulties for international treaty formation than perhaps any other form of governance. Federal constitutions that grant subnational governments virtually exclusive regulatory authority over certain subject matter may constrain national governments during international negotiations—a national government that cannot constitutionally bind subnational governments to an international agreement cannot freely arrange its international obligations. While federal nations that grant subnational governments exclusive regulatory control obviously place value on stringent decentralization and the benefits it provides in those regulatory areas, the difficulty lies in striking a balance between global governance and constitutional decentralization in federal systems. Recent scholarship demonstrates that U.S. federalism, for example, may jeopardize international negotiations seeking to utilize certain mechanisms of global forest management to combat climate change, since subnational forest management is a regulatory responsibility reserved for state governments under current constitutional jurisprudence. This Article expands that scholarship by undertaking a comparative constitutional analysis of five other federal systems—Australia, Brazil, Canada, India, and Russia. These nations, along with the United States, are crucial to climate and forest negotiations since they account for 54% of the world’s total forest cover. This Article reviews the constitutional allocation of forest regulatory authority between national and subnational governments in these nations to better understand potential complications that federal systems present for global climate governance aimed at forests. The Article concludes that federal systems maintaining three key elements within their constitutional structure are most capable of agreeing to an international climate agreement that incorporates forests in a consequential manner—elements that facilitate successful implementation of a treaty on domestic scales while maintaining the recognized benefits of decentralized forest management at the local level: (1) national constitutional primacy over forest management, (2) national sharing of constitutional forest management authority, and (3) adequate forest policy institutional enforcement capacity. The Article also establishes the foundation for further research assessing how the constitutional status quo of federal systems lacking key elements may be adjusted to achieve more effective climate and forest governance.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.006 | 0.025 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 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".