Sraffa and the problem of returns : a view from the Sraffa archive
Bibliographic record
Abstract
About a quarter of a century ago, Carlo Panico and one of the authors of this chapter published a paper on ‘Sraffa, Marshall and the problem of returns’ (EJHET 1994) in which they explored links between Sraffa’s mid-1920s critique of Marshallian economics and the analysis developed some 35 years later in Production of Commodities. The 1994 contribution focused exclusively on Sraffa’s published works since his unpublished manuscripts were not yet freely accessible. With the benefit of hindsight, it may be claimed that Sraffa was a scholar who, during his lifetime, published little but wrote a lot (Kurz, 2008). Hence, when in December 1994 Trinity College Cambridge, UK, opened the Sraffa Archive, a huge amount of hitherto unknown material became available to the scientific community. Our aim in this chapter is to reconsider some of the results achieved in the 1994 contribution in the light of the new evidence provided by Sraffa’s manuscripts. The 1994 paper investigated four issues: (i) the chronological development of Sraffa’s thought in the second half of the 1920s, (ii) the analysis of the firm in the 1920s and in 1960, (iii) the determinants of variable returns in the 1920s and in 1960 and, finally, (iv) interdependence among sectors and the assumption of given quantities. In this chapter, we focus on the last two issues since, as regards item (ii), we were not able to find elements of interest in the Sraffa Archive while Garegnani (2005) and Kurz and Salvadori (2005a) have provided a thorough scrutiny of unpublished material related to item (i).
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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 | 0.027 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.009 |
| Science and technology studies | 0.006 | 0.025 |
| Scholarly communication | 0.016 | 0.028 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.007 | 0.011 |
| Insufficient payload (model declined to judge) | 0.014 | 0.003 |
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".