Shake and Bake: Exploring Drug Producers’ Adaptability to Legal Restrictions Through Online Methamphetamine Recipes
Bibliographic record
Abstract
Despite numerous regulations, methamphetamine consumption persists; its availability has even increased in the United States. Methamphetamine is produced in small labs and super labs that are differentiated by the quantity of drug they generate and by how they are embedded in trafficking networks. The stagnant statistics regarding methamphetamine consumption and lab seizures suggest that laws have been ineffective, partly due to the producers’ adaptability. To understand this adaptation, methamphetamine recipes collected online will be analyzed through a qualitative methodology. Emphasis will be placed on the impact of the American legislation toward synthetic drug production. This article describes how methamphetamine producers have adapted to get around the regulations. The producers synthesize the regulated precursors by extracting them from processed products. To comply with the quotas imposed by law, the producers limit their quantities used. This article suggests that producers keep abreast of legislations and perfect the recipes accordingly.
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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 | 0.008 | 0.026 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.005 | 0.006 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".