Economic Policy with and without Maximizing Rules
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract This paper contrasts the static neoclassical and the evolutionary views of the economy and economic policy. It responds to Ng's comments on Lipsey's original criticism of third‐best theory. Under a relevant definition of informational poverty and Ng's other assumptions, the expected value of any policy‐created divergence from the status quo is negative: If there is not enough known to determine what to do, nothing should be done, rather than establishing first‐best conditions as Ng's analysis has it. It is argued that Ng's analysis of his two other information states adds little to what common sense suggests. To address Ng's argument that policies using context‐specific objective functions lack the required welfare basis, the present paper studies how economic policy is actually pursued absent guides provided by welfare economics. Policies that follow from evolutionary economic theory imply that many things that are seen as ‘distortions’ in welfare economics are actually desirable forces that drive economic growth.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.007 |
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 it