Mexico's methamphetamine precursor chemical interventions: impacts on drug treatment admissions
Bibliographic record
Abstract
AIMS: To help counter problems related to methamphetamine, Mexico has implemented interventions targeting pseudoephedrine and ephedrine, the precursor chemicals commonly used in the drug's synthesis. This study examines whether the interventions impacted methamphetamine treatment admissions-an indicator of methamphetamine consequences. DESIGN: Quasi-experiment: autoregressive integrated moving average (ARIMA)-based intervention time-series analysis. INTERVENTIONS: precursor chemical restrictions implemented beginning November 2005; major rogue precursor chemical company closed (including possibly the largest single drug-cash seizure in history) March 2007; precursor chemicals banned from Mexico (North America's first precursor ban) August 2008. SETTINGS: Mexico and Texas (1996-2008). MEASUREMENTS: Monthly treatment admissions for methamphetamine (intervention series) and cocaine, heroin and alcohol (quasi-control series). FINDINGS: The precursor restriction was associated with temporary methamphetamine admissions decreases of 12% in Mexico and 11% in Texas. The company closure was associated with decreases of 56% in Mexico and 48% in Texas; these decreases generally remained to the end of the study period. Neither intervention was associated with significant changes in the Mexico or Texas quasi-control series. The analysis of Mexico's ban was indeterminate due largely to a short post-ban series. CONCLUSIONS: This study, one of the first quasi-experimental analyses of an illicit-drug policy in Mexico, indicates that the country's precursor interventions were associated with positive impacts domestically and in one of the Unites States' most populous states--Texas. These interventions, coupled with previous US and Canadian interventions, amount to a new, relatively cohesive level of methamphetamine precursor control across North America's largest nations, raising the possibility that the impacts found here could continue for an extended period.
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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 | 0.001 | 0.003 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".