Sīdhu (Śīdhu): the Sugar Cane “Wine” of Ancient and Early Medieval India
Bibliographic record
Abstract
This article considers the nature of one particular drink made from sugar cane called sīdhu (usually m., also śīdhu), exploring the evidence from textual sources. Other drinks were made with sugar cane products, such as āsavas, medicinal ariṣṭas, and the drink called maireya, but I will not consider those here. As I argue, sīdhu was the basic fermented sugar cane drink, not strongly characterized by additives—“plain” sugar-wine as it were. Though in a manner typical of premodern Indic alcohol culture, even this one drink was a complex and variable affair. Rather than consider this drink in medical sources alone—important as that evidence may be—my methodology here is to examine the history of this drink in the light of a wide range of textual evidence, placing this drink in the broad context of pre-modern South Asian drinking culture.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.013 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".