Bruce E. Baker and Barbara Hahn. <i>The Cotton Kings: Capitalism and Corruption in Turn-of-the-Century New York and New Orleans</i> .
Bibliographic record
Abstract
What do cotton, Canada, and Mardi Gras krewes have in common? If you read The Cotton Kings: Capitalism and Corruption in Turn-of-the-Century New York and New Orleans you will find out. Bruce E. Baker and Barbara Hahn have written an insightful, useful, and interesting book that blends the histories of business, the South, society, politics, and the environment. In this “economic drama” they argue that the cotton market at the turn of the twentieth century worked better when it was regulated (1). By the late 1800s, there were two cotton exchanges in the U.S., one in New Orleans and the other in New York. Traders in both places made futures trades, which were essentially bets as to whether the price of cotton would rise or fall. The price of futures began to affect the spot, or immediate sales, usually by inhibiting prices. Bear traders in New Orleans worked to drive up prices while their counterparts in New York, the bulls, strove to drive down prices. A complicating factor was the lack of information about cotton forecasts. Bulls typically created, or at least publicized, reports that pointed to a bumper crop. Such rosy forecasts tended to drive down prices.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.011 | 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".