Bibliographic record
Abstract
For decades, we have debated whether “political safeguards” preserve healthy relations between the states and the federal government and thus reduce or eliminate the need for judges to referee state–federal tussles. No one has made such an argument about relations among the states, however, and the few scholars to have considered the question insist that such safeguards don’t exist. This Article takes the opposite view and lays down the intellectual foundations for the political safeguards of horizontal federalism. If you want to know what unites the burgeoning work on horizontal federalism and illuminates the hidden logic of its doctrine, you need know only one fact: lawyers hate spillovers. Whether it is a state’s decision to license same-sex marriage or set high emissions standards or maintain lax gun-ownership rules, we worry when one state’s regulations affect residents in another state. And just as most scholars aspire to prevent spillovers, most look to the courts to fix the problem. The current state of the law and literature makes clear why no one has thought to develop a safeguards account of horizontal federalism to match the one that dominates debates over vertical federalism. Why bother with political safeguards if politics is the problem and the judiciary is the solution? In this Article, we don’t just question the consensus against spillovers but offer an affirmative account as to why much interstate conflict can or should be left to the free play of politics. Our argument emphasizes the democratic possibilities associated with spillovers and looks to vertical federalism as a model for thinking about how the states ought to interact with each other. Spillovers, after all, occur just as routinely between the state and federal government as they do between the states. State–federal friction, however, is understood to be both a problem and a valuable part of a well-functioning democracy. The same should be true of horizontal federalism. Our goal should not be to suppress friction but to harness it—to shut down damaging spillovers while allowing productive ones to run their course.
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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 | 0.009 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.026 |
| Scholarly communication | 0.008 | 0.008 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.005 | 0.010 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".