Frank Ramsey’s place in the history of mathematical economics: not what you think
Bibliographic record
Abstract
Abstract Frank Ramsey is a towering figure in economics. His two papers published in the 1920s are responsible for his reputation as a pioneer in mathematical economics. Economists and historians of economics disagree on how to read Ramsey. One point of contention is whether he introduced the use of a representative agent or instead employed a social welfare function. We intend to clarify this question by further complicating it. It is clear from archival materials, including a previously undiscovered paper (‘Mathematical Economics’), that he was not a trailblazer in mathematical analyses of economic questions. Ramsey was a socialist who was inclined to theories of value and psychology that went beyond utility. He struggled with the tension between what is good for the individual and what is good for society. He was sure that utilitarian psychology was not an accurate basis for economics and he was sceptical of its idealizations.
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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 | 0.007 | 0.022 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.017 |
| Scholarly communication | 0.005 | 0.016 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.004 | 0.012 |
| Insufficient payload (model declined to judge) | 0.005 | 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".