Popping the Balloon Effect: Assessing Drug Law Enforcement in Terms of Displacement, Diffusion, and the Containment Hypothesis
Bibliographic record
Abstract
The "balloon effect" is an often used but rather dismissive representation of the effects of drug law enforcement. It implies a hydraulic displacement model and an impervious illicit drug trade. This paper reviews theoretical and empirical developments in policing and crime prevention. Based on this, 10 types of displacement are identified and four arguments developed: (1) Displacement is less extensive and harmful than often contended; (2) Where displacement may occur it preferably should be exploited as a policy tool to delay the illicit drug industry and deflect it to less harmful locations and forms; (3) The opposite of displacement occurs, termed a diffusion of drug control benefits, wherein law enforcement has benefits that extend further than envisaged, and has 10 types mirroring those of displacement; (4) The net impact of drug law enforcement is often underestimated, and a containment hypothesis may offer a more accurate framework for evaluation.
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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 | 0.023 | 0.093 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.001 | 0.012 |
| Scholarly communication | 0.002 | 0.009 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.003 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".