Shake and Bake: Exploring Drug Producers’ Adaptability to Legal Restrictions Through Online Methamphetamine Recipes
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
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.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 it