Bibliographic record
Abstract
David Hume's essays were “the cradle of economics,” suggested John Hill Burton, in his important biography of Hume. Although this may be a biographer's exaggeration, there can be no doubt that Hume's work provided an important contribution to political economy as a discipline, together with a significant critique of the “mercantile” system that was later attacked by his friend Adam Smith. ECONOMICS: THE BACKGROUND Mercantilism is difficult to define. As the historian P.J. Thomas put it: “Mercantilism has often been described as a definite and unified policy or doctrine, but that it has never been. In reality it was a shifting combination of tendencies which, although directed to a common aim - the increase of national power - seldom possessed a unified system of policy, or even a harmonious set of doctrines. It was a very complicated web of which the threads mingled inextricably.” In the seventeenth and eighteenth centuries the object of policy was the enhancement of the power of the nation state, a strategy that was to be attained in a number of ways, at least one of which was economic. The power of this state was to be enhanced by the accumulation of treasure through trade, the maximization of employment, and the encouragement of population growth.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.014 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 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".