Bibliographic record
Abstract
The assumption of a single price at any time is very generally imposed on market theorizing. It is unrealistic, but generally accepted because of the needs of welfare theory, and of current theoretical methods. In order to evaluate the significance of the loss in realism from the use of this assumption, it seems to be worthwhile to start with the other extreme of complete ignorance in a market, and allow buyers and sellers to pair off at random, allowing a diversity of prices. It is very interesting that in such a "blind market" the quantity traded tends to be larger, by about 44 per cent. The theory of such a market can be based on a Marshallian industry, and many different versions are suggested. The theory does seem to give useful insight into the results of imposing uniform pricing by barbers, and uniform wage rates in labour markets. The loss in trade and employment seems to be great enough that we should examine a little more carefully the arguments that have been accepted so easily that such uniformity implies greater equity.
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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 | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.016 |
| Scholarly communication | 0.006 | 0.012 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.008 | 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".