Conflict Management in Illicit Drug Cryptomarkets
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
Illegal drug markets have been described as “stateless” systems. Drug dealers, moreover, are commonly considered to have a predilection toward the use of violence to resolve disputes arising from dealing activities. While some studies have undermined this popular perception, new trends surrounding the distribution of illegal drugs via online channels (drug cryptomarkets) have shifted the transactional setting from the physical to virtual realm, thus decreasing the likelihood of violent resolution outcomes even further. This article examines conflict management strategies within cryptomarkets by coding discussion forums between vendors and buyers. Violence, as expected, is absent. Strategies more likely reflect alternatives that have been recognized in conflict management research within and beyond illegal market settings: tolerance, avoidance, ostracism, third-party intervention, negotiation, and threats. The overall setting from which such resolutions emerge is clearly not subject to formal regulations, but our analyses illustrate the multitude of informal social control mechanisms that are consistently at play and which underlie the self-regulatory and communal processes that are firmly in place.
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 | 0.000 |
| 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 | 0.001 |
| Open science | 0.002 | 0.001 |
| 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