Wirtschaftliche Analyse der Folgen einer Legalisierung von Cannabis in Deutschland
Bibliographic record
Abstract
The international debate on cannabis legalization gained considerable momentum after US states Colorado and Washington adopted laws on legal recreational cannabis for the first time. Ever since, seven US states and nations such as Uruguay and Canada followed the lead. Germany is no exception from this development and there are various other countries considering to legalize marihuana for recreational purposes as well. It is of high interest for policy makers in politics, economics and public health and safety to understand to what extent such an amendment influences different areas of society. The academic literature about coherent implications for the German state is scarce. The present thesis is an analysis of the economic consequences of a potential cannabis legalization in Germany and a weighing up of its pros and cons in monetary terms. Information about properties of cannabis markets such as supply, prices, demand and their dynamics - predominantly from scientific research in nations with adopted legalization or decriminalization laws – were examined and transferred to Germany to compute likely income and expenditure related to or influenced by cannabis. Factors included are demand reactions and thereby impacts on tax income from marihuana, public expenditure for law enforcement and health, the alcohol industry, opiate consumption, as well as road safety and drug-related crime. A legalization would result in a significant increase of annual cannabis consumption and regular users in Germany. The analysis identified public expenditure and tax income as substantial components with regard to the economic feasibility study. Interrelations to alcohol consumption are also important in determining the appropriateness of such an amendment. Severe adverse outcomes on road safety or other drug consumption are not expected. Drug-related crime and power of organized crime are likely to decrease.
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How this classification was reachedexpand
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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.001 | 0.005 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".