Beyond China’s drug century: Yunnan’s first therapeutic community and narratives of drug treatment and mental health care
Bibliographic record
Abstract
China is experiencing rapid cultural change and new forms of sociability that are accompanied by social problems and novel humanitarian interventions that have been formulated to address those problems. The pressure related to the rapid transformation of the countryside into mid-level cities has led to recreational drug-use as a means of escape. These illegal drugs have greased the wheels of what I call an affective biopolitics that has influenced Chinese citizens. Carlos Rojas argues that development in China results from the effects of discrete protocols, or practices that stem from tensions between capital and labor, governmentality and biopolitics, and nationalism and globalization. To tease out the particulars of Rojas' protocols and practices, in this article, I first review two historical periods: 1) the rise and fall of opium consumption in the early 19th century, and 2) the 21st-century psychology boom. I use these two literature reviews to set the stage to discuss my ethnographic study of Sunlight, China's first residential therapeutic community for drug users in Yunnan Province. Sunlight's residents and founders provide a unique window into local everyday drug use at a particular time in China's economic boom, from 2007 through 2015. We know much about China's opium century but very little about the contemporary context, new consumers who partake in pleasure-consuming drugs, or the reformers who address these 21st-century public health issues.
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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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.017 | 0.018 |
| Scholarly communication | 0.005 | 0.006 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.001 | 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".