Bibliographic record
Abstract
After President Trump announced that the United States would withdraw from the Paris climate agreement, Governor Brown issued a joint statement with his counterparts from New York and Washington, announcing that the three governors “are teaming up to fight climate change in response to President Trump’s” withdrawal decision. A few days later, Governor Brown met in Beijing with China’s President Xi Jinping. The Chinese President reportedly “welcomed California’s efforts to work with the Chinese government to help combat global warming.” According to the California government web site, the state is party to a total of 54 “international agreements” on climate change, including agreements with both national and sub-national governments.Governor Brown’s international diplomacy raises two distinct constitutional concerns. First, the Compact Clause provides: “No State shall, without the Consent of Congress . . . enter into any Agreement or Compact . . . with a foreign Power.” California’s cap-and-trade agreement with the Government of Québec (the “Linking Agreement”) is vulnerable to a constitutional challenge in this respect. Second, the Foreign Commerce Clause grants Congress power “to regulate Commerce with foreign Nations.” The Supreme Court has held that state laws may violate the Dormant Foreign Commerce Clause if they “prevent this Nation from ‘speaking with one voice’ in regulating foreign commerce.” The Linking Agreement may also run afoul of the Dormant Foreign Commerce Clause. Although the matter is not free from doubt, I conclude that the Linking Agreement does not violate the Dormant Foreign Commerce Clause. However, the Agreement may be unconstitutional under the Compact Clause, absent congressional consent. The Conclusion considers options available to Governor Brown to mitigate potential constitutional difficulties.
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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.006 | 0.004 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.008 |
| Insufficient payload (model declined to judge) | 0.015 | 0.002 |
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".