Oil, Wine, and the Cultural Economy of Ancient Greece : From the Bronze Age to the Archaic Era
Bibliographic record
Abstract
"Chapter 1 Introduction "There are two liquids most pleasing to human bodies: inside-wine, outside-oil." -Pliny (23-79 CE), Natural History XIV, 29.150 "It is evident that the country now called Hellas had in ancient times no settled population ... without commerce, without freedom of communication either by land or sea, cultivating no more of their territory than the exigencies of life required, destitute of capital, never planting their land ... " -Thucydides (c. 460-400 BCE), History of the Peloponnesian War, 1.2.1-2 Oil, Wine, and Cultural History in Pre-Classical Greece This book aims to explore the centrality of olive oil and wine in various realms of ancient Greek life and how this interdependence came to exist and persist. Indeed, this book argues that oil and wine can be regarded not just as economic commodities, but cultural commodities that actively shaped the paths of ancient Greek history. Cultural commodities can be defined as things that have become deeply entangled with humans through increasing ties of dependency that are reinforced by a high value constructed within multiple contexts of exchange. On the one hand, expansions and contractions of dependencies between people and oil/wine can be seen by tracing shifting emphases in exchange modes-such as commensal, gift, and commercial exchange-within their social and environmental contexts over the long-term"--
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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".