Bibliographic record
Abstract
Notes on contributors Preface Introduction: Culture, consumption and society Andrew Sherratt, University of Oxford 1. Alcohol and its alternatives: symbol and substance in pre-industrial cultures Andrew Sherratt 2. Coca, beer, cigars and yag'e: meals and anti-meals in an Amerindinian community Stephen Hugh-Jones, University of Cambridge 3. Nicotian Dreams: the prehistory and early history of tobacco in eastern North America Alexander von Gernet, University of Toronto 4. Efficacy and concentration: analogies in betel use among the Fuyage (Papua New Guinea) Eric Hirsch, Brunel University 5. Kola nuts: the 'coffee' of the central Sudan Paul E. Lovejoy, York University, Canada 6. EXCITANTIA: Or, how enlightenment Europe took to soft drugs Jordan Goodman, University of Manchester Institute of Science and Technology 7. From coffeehouse to parlour: the consumption of coffee, tea and sugar in northwestern Europe in the seventeenth and eighteenth centuries Woodruf D. Smith, University of Texas at San Antonio 8. Tobacco use and tobacco taxation: a battle of interests in early modern Europe Jacob M. Price, University of Michigan 9. Japan and the world narcotics traffic Kathryn Meyer, Lafayette College, Pennsylvania 10. The rise and fall and rise and fall of cocaine in the United States David T. Courtwright, University of North Florida Afterword Jordan Goodman and Paul E. Lovejoy Selected bibliography Index
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.593 | 0.331 |
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".