Leader to Laggard: How Founding Institutions Have Shaped American Environmental Policy
Bibliographic record
Abstract
The U.S. led the world in environmental policy in the 1970s, but now lags behind comparable nations and resists joining others in tackling climate change. Two embedded, entwined, and exceptional American institutions—broad private property rights and competitive federalism—are necessary for explaining this shift. These two institutions shaped the exceptional stringency of 1970s American environmental laws and the powerful backlash against these laws that continues today. American colonies ensured broad private rights to use land and natural resources for profit. The colonies and the independent state governments that followed wielded expansive authority to govern this commodified environment. In the 1780s, Congress underwrote state governance of the privatized environment by directing the parceling and transfer of federal land to private parties and of environmental governance to future states. The 1787 Constitution cemented these relationships and exposed states to interstate economic competition. Environmental laws of the 1970s imposed unprecedented challenges to the environmental prerogatives long protected by these institutions, and the beneficiaries responded with a wide-ranging counterattack. Federalism enabled this opposition to build powerful regional alliances to stymie action on climate change. These overlooked institutional factors are necessary to explain why Canadian and American environmental policies have diverged.
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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 | 0.005 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.013 | 0.017 |
| Scholarly communication | 0.009 | 0.006 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 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".