Bibliographic record
Abstract
This chapter examines the ideas of neomercantilist thinkers from outside Europe and the United States whose thought became well known in various places during the pre-1945 period. Some of them adapted the ideas of neomercantilist thinkers from Europe and the United States in creative ways, including thinkers from Argentina (Alejandro Bunge), Australia (David Syme), China (Liang Qichao), Ethiopia (Gabrahiwot Baykadagn), India (Mahadev Govind Ranade, Benoy Sarkar), and Turkey (Ziya Gökalp). Others developed distinctive neomercantilist ideas without much, or any, reference to neomercantilist thought from Europe and the United States, including figures from Canada (John Rae), China (Sun Yat-sen, Zheng Guanying), Egypt (Muhammad Ali), Japan (Fukuzawa Yukichi, Ōkubo Toshimichi), and Korea (Yu Kil-chun). This latter group of thinkers reveal how the ideas of Hamilton and List did not play the same kind of central role in the emergence of neomercantilist thought that Smith’s played in the growth of economic liberalism. Taken together, all the thinkers described in this chapter reinforce the point that neomercantilist thought was characterized by considerable diversity.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.004 | 0.009 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.013 | 0.004 |
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".