Javier BLAS and Jack FARCHY, The World for Sale: Money, Power, and the Traders Who Barter the Earth’s Resources
Bibliographic record
Abstract
The World for Sale: Money, Power, and the Traders Who Barter the Earth’s Resources sheds light on commodity traders, crucial yet often overlooked actors in the global economy. The book is a collection of stories about them, how they get involved in political affairs, where they get their power, and how they work in the shadows. These stories from different times and places show the immense power of commodity traders. Methodologically, the book is mainly based on interviews with more than a hundred traders. Blas and Farchy also collected thousands of pages that detail the finances, business networks, and structure of commodity traders’ organizations (p. 11-12). The book consists of 13 chapters. Chapters 2, 3, and 4 are particularly important since they reveal how commodity traders operate by addressing the energy crisis that arose due to waves of nationalization in the Middle East in the 1970s and 1980s. The book’s main purpose is to reveal the role of despots and tyrants in the global economy by pointing out the unsavory aspects of their businesses, such as bribery and offshore banking. Since most of these methods are illegal and cannot be used by official companies and institutions, such commodity traders come to the fore.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.005 | 0.007 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.012 | 0.003 |
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".