Pragmatic Suggestions on Germany’s Cannabis Legalization Policy Under the new Federal Government Towards Protecting Public Health and Safety
Bibliographic record
Abstract
Abstract: Background: Germany’s previous federal government coalition (SPD-The Greens-FDP) implemented the legalization policy for non-medical cannabis use and supply on 1 April 2024. The in 2025 newly elected federal government, led by the CDU, originally intended to revert this policy, but then decided to continue on with it for the time being. Results/Conclusions: In this brief position paper, we present three elementary suggestions as to how – based on the current state of scientific knowledge – the cannabis legalization policy would best be moved forward in Germany with a primary focus and aim on protecting public health.
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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 | 0.024 | 0.030 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.006 | 0.009 |
| Scholarly communication | 0.011 | 0.009 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.023 | 0.010 |
| Insufficient payload (model declined to judge) | 0.014 | 0.002 |
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".