Bibliographic record
Abstract
Sheila Dow has made substantive and sustained contributions to Post-Keynesian thinking, the methodology of economics, and the history of economic thought. This chapter focuses on the latter, and in particular Dow’s engagement with the Scottish political economy tradition. Together with colleagues and her husband, Alistair, Dow has done much to explore and reveal the nature and on-going relevance of this tradition. It is an important influence on Dow’s thinking in macroeconomics and economic methods. Indeed, Dow’s approach is the modern embodiment of this tradition. Scottish political economy may be traced to Enlightenment thought, which in Scotland revolved around four strands: natural law philosophy, a historical approach to analysis, “common-sense” philosophy, and “moderate” scepticism. For Dow, Scottish political economy reflects these elements through its emphasis on, for example, history, fallibilism, and an understanding of individuals as social beings. I argue that Dow does much to reinvigorate this tradition and its relevance. In doing so, however, she overlooks an emphasis on social provisioning in the tradition. For instance, Steuart and Smith identify provisioning as a key element of economic activity, which establishes a hierarchy of goods. This serves as a basis of challenge to modern standard economics’ moral equivalence of goods. Acknowledging social provisioning strengthens Dow’s argument about the continuing relevance of the Scottish political economy. JEL Codes: B10; B12; B15; B30
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.007 |
| Scholarly communication | 0.005 | 0.006 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".