Where MLM Intersects MFA: Morally Suspect Goods and the Grounds for Regulatory Action
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
The market failures approach (MFA) to business ethics argues that economic theory regarding the efficient workings of a market can generate normative prescriptions for managerial behaviour. It argues that actions that inhibit Pareto optimal solutions are immoral. However, the approach fails to identify goods that should be regulated or prohibited from the market, something common to the moral limits to markets (MLM) approach to business ethics. There are, however, numerous assumptions underlying Paretian efficiency, including some about the preferences of market participants. Trade in some goods violates some of these assumptions, and so these goods are morally suspect and can be understood to indicate that the market for these goods is not moral. This creates grounds sufficient for regulating, and possibly prohibiting, these goods. To help determine whether it is then necessary to regulate the goods, I propose a supplementary economic analysis to ascertain why an assumption regarding a particular preference is being violated.
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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 | 0.007 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it