Bibliographic record
Abstract
The transnational corporations (TNCs) are portrayed as the main instruments of globalization, although they are by no means a new phenomenon. TNCs emerged quite early, in the seventeenth century. The Vereenigde Ost-indische Compagnie, alias the East India Company, was born in 1602, and was trading cottons from Coromandel to Indonesia and China, silks from China, Tonkin, India, and Persia to Manila and on to New Spain (Mexico), tea and gold from China, coffee from Mocha, and asserted itself as the world’s only supplier of nutmeg, cloves, and mace (Landes, 1998: 141–5). The Hudson Bay Company was founded in 1677, and traded furs from Canada to Europe. In the late nineteenth century multinationals such as Singer Sewing Machines, International Harvester, American. Bell, Standard Oil of New Jersey, Ciba, Hoescht, BASF, Siemens, and Royal-Dutch Shell started trading. Yet they were still exceptions.
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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.003 | 0.009 |
| Scholarly communication | 0.010 | 0.013 |
| Open science | 0.001 | 0.009 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.012 | 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".