Exploring the Defensive Actions of Drug Sellers in Open-air Markets
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
Objectives: The current study contributes to the literature through a systematic social observation of the defensive actions of drug sellers within open-air retail markets. The study expands upon previous literature by incorporating a novel data collection and coding method. Methods: Video footage of narcotics transactions was extracted from the closed-circuit television (CCTV) system of the Newark, NJ Police Department. Researchers transcribed and coded the footage to measure the frequency of defensive actions incorporated by drug sellers. Fisher’s exact tests measured whether the frequency of each defensive action significantly differed across geographic setting or time of day. Results: The frequency of many defensive actions was significantly related to geographic setting and time of day. The strongest relationship was observed between the use of stash spots and setting. Overall, the findings suggest that drug sellers adopt tenets of Opportunity Theory to protect themselves from law enforcement, specifically by acting as guardians and place managers on their own behalf. Conclusions: This study extends prior techniques and provides an additional case study on the use of CCTV footage in the study of street-level crime. This methodology can be used in concert with more traditional ethnographic techniques in the study of the drug trade and in crime-and-place research in general.
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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 | 0.008 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.000 |
| 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