Why Michigan v. EPA Requires that the Meaning of the Cost/Rationality Nexus Be Clarified
Bibliographic record
Abstract
This article examines the recent decision in Michigan v. EPA, in which the U.S. Supreme Court held that the EPA acted unreasonably in not considering costs at the listing phase of the regulation of power plants’ emissions under a specific provision of the Clear Air Act (CAA). In Michigan, the Court interpreted the applicable statutory provision based on the principles of rational administrative decision-making, thereby establishing a connection between cost consideration by administrative agencies and the principles of reasonable exercise of administrative discretion. We contend that Michigan failed to properly appreciate the logical and axiological connection between cost consideration and administrative rationality (i.e., the cost/rationality nexus). More specifically, the Court failed to distinguish between two independent steps of cost consideration: cost determination and cost quantification. Cost determination considers that one set of relevant interests must be made a cost upon someone else, and decides how to allocate rights between competing interests. This decision rests on political considerations and moral factors that are independent of the concept of cost. Cost quantification requires deliberating to what extent one set of interests should be made a cost upon someone else. Unlike cost determination, cost quantification is logically based on the concept of cost. Cost quantification assumes cost determination in order to function. The failure to appreciate this distinction led to illogical reasoning by the Court and to a decision that is inconsistent with Congress’ cost determination. This paper contributes to the legal-economic literature on cost-benefit analysis (CBA) by outlining a functional dimension of cost consideration by administrative agencies that is frequently overlooked in legal-economic literature. While CBA proponents often note that cost consideration provides agencies with a method for promoting social welfare maximization, we emphasize that cost consideration enhances the rationality of administrative action by ensuring a transparent and accountable definition of the set of relevant interests that underpins the definition of costs and benefits.
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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 | 0.008 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.015 |
| Scholarly communication | 0.008 | 0.012 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.018 | 0.015 |
| Insufficient payload (model declined to judge) | 0.009 | 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".