Alcohol in the Early Modern World: A Cultural History, ed. B. Ann Tlusty
Bibliographic record
Abstract
B. Ann Tlusty has commissioned eight unique essays to offer a summary of current knowledge about the place of alcohol in the lives of people from the sixteenth through to the late eighteenth century. The authors are established, active scholars who, in short chapters, summarise the state of work on alcohol and consumption, production, regulation, trade, medical use, sexuality and gender, religion and representation of drink in the period. Each chapter enjoys copious citation from primary and secondary sources. There is a combined, extensive and up-to-date bibliography, valuable in and of itself since the last three decades have seen extensive research on the topics under consideration. One goal of the volume is to be global but, though a number of the authors offer information about drink in Latin America and Africa, the concentration is on Europe and especially on Germany and England. Eastern Asia gets very limited attention. The range of drinks discussed is wide, from the obvious standards of the Middle Ages (that is, beer and wine) to distilled products starting with brandy and then extending to rum and later gin, but also encompasses less commonly discussed regional drinks such as chicha, a Peruvian drink made from fermented grains, and cachaça, a distilled drink derived from sugar production popular both in Brazil and west Africa, among a number of others.
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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 | 0.004 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 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".