Bibliographic record
Abstract
The emergence of classical economic liberalism was much more than just a European story. Economic liberal thought found supporters among thinkers from many other parts of the world in the nineteenth and early twentieth centuries, many of whom also adapted it in various ways in response to their local circumstances. This chapter highlights adaptations made by prominent thinkers from the Americas (Thomas Cooper, José da Silva Lisboa, Manuel Pardo y Lavalle, Carlos Calvo, Harold Innis), South Asia (Rammohun Roy, Dadabhai Naoroji), Africa and the Ottoman Empire (Olaudah Equiano, Alexander Crummell, Hassuna D’Ghies), as well as East Asia (Taguchi Ukichi, Yan Fu). The ideas of some of these figures also found an audience in Europe, revealing that liberal ideas flowed not just from Europe to the rest of the world but also in the other direction. Further, some economic liberals outside Europe questioned the European origins of this perspective by claiming its independent roots in their own region. In the Chinese case, the chapter also describes how a contemporary of Adam Smith’s, Chen Hongmou, developed ideas that bore some similarities to European economic liberalism without knowledge of the latter.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.009 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 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".