Cannabis, Lord Shiva and Holy Men: Cannabis Use Among Sadhus in Nepal
Bibliographic record
Abstract
Background: Despite being illegal in Nepal, cannabis grows wild, is cultivated, readily available and often consumed during religious festivals, such as those in honour of the Hindu god Shiva. Holy men (sadhus) also consume cannabis to aid meditation, and many are believed to suggest that as a substance favoured by Lord Shiva, and, as such, should be used. However, there are concerns that all cannabis use in Nepal is not benign, and that there are negative health and social consequences from its use for some consumers. Objectives: This study sought the views of sadhus in Nepal.Method: During the major Shiva festival at Pashupathinath temple complex in Kathmandu, Nepal, 200 sadhus were surveyed. Results: Most used cannabis daily, a quarter believed cannabis and its use to be legal in Nepal, and a further ten percent were unsure, about one third believed cannabis should be used by Hindus, but only fourteen believed Lord Shiva promoted its use. Those less educated and from the Naga sect were more likely to hold such views, and provide cannabis to devotees. Conclusions: Sadhus with evidence-based information about cannabis and its potential harms can play an important role in assisting to reduce harm and facilitate engagement in treatment. J Psychiatric Association of Nepal Vol .3, No.2, 2014, pp:9-14DOI: http://dx.doi.org/10.3126/jpan.v3i2.12379
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".