David A. Guba Jr. <i>Taming Cannabis: Drugs and Empire in Nineteenth-Century France</i>; Benjamin Breen. <i>The Age of Intoxication: Origins of the Global Drug Trade</i>.
Bibliographic record
Abstract
Two exciting new books, David Guba Jr.’s Taming Cannabis: Drugs and Empire in Nineteenth-Century France and Benjamin Breen’s The Age of Intoxication: Origins of the Global Drug Trade, trace the rise of the globalized drug economy in Western Europe and its relationships to colonial empire (1600–1900), connecting Europe to the Americas, Africa, and India, and to the construction of drugs in European imaginaries. These cultural histories describe drugs as social constructs, embedded in specific Portuguese, Spanish, English, and French ideas of race, politics, law, colonial empire, and commerce. We discover cultural reasons why some pharmacodynamic plants have become lawful medications and others illegal drugs, and how European publics experienced the expansion and globalization of pharmacy from the early modern period to the present. A feast for the mind and a delight to the eye, Breen’s intellectually ambitious The Age of Intoxication takes the reader on a world tour of early modern drugs in imperial Europe, their identification, sale, and trade in colonial and exotic lands, and the intersections with cultural valuation and law that produced the licit and the illicit. Breen intertwines this history with the global Portuguese Empire, the Columbian Exchange, transatlantic slavery, the Scientific Revolution, the Inquisition, and finally the British empire. A work of big ideas, Breen moves between chapters dedicated to historical examples—quina in the Amazon, intoxicants in West Africa, opium in the Indian Ocean, and crypto-Jewish and African apothecaries in Spain. Some readers may feel the argumentative reach occasionally exceeds the evidentiary grasp, but with its masterful use of sources and provocative arguments, Breen’s book will open new avenues for scientific historians.
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.021 | 0.009 |
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".