A Novel Method for Measuring the Extent of Cocaine Flows Across the U.S
Why this work is in the frame
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Bibliographic record
Abstract
We propose a novel method to measure the spatial extent of cocaine flows in the US using data on the price and purity of cocaine observed in drug seizures or undercover drug purchases. We then compare the cocaine trafficking network extracted using this method to anecdotal knowledge about cocaine flows using network analytic methods. Based on the network analysis, the trafficking networks inferred from price and purity data appear to be more elaborate in their geographic extent than prior anecdotal evidence suggests. The analysis uncovers previously unrecognized flows, notably identifying multiple possible cocaine source points along the US-Canadian border, challenging the traditional and likely incomplete narrative focused on the southern border. This study demonstrates that variation in cocaine purity across space and over time can help detect unconventional patterns of cocaine flows, complementing the conventional understanding of the extent of cocaine flows.
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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 | 0.002 | 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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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