Analysis of Public Policy Processes in Multiple Streams Framework and Advocacy Coalition Framework: Is Canada's Decriminalization Policy for Drugs Reasonable?
Bibliographic record
Abstract
This paper analyzes the rationale for Canada's drug decriminalization policy through the multiple streams framework (MSF) and the advocacy coalition framework (ACF). Canada attempts to decriminalize small amounts of drug possession in response to the growing opioid crisis. This paper also uses MSF to explain how the problem stream, policy stream, and political stream have created a policy window for the introduction of drug decriminalization policies, while ACF reveals the conflicting beliefs of different advocacy coalitions and their important roles in policy evolution. The analysis shows that MSF is more suitable for explaining the timing and dynamics of drug decriminalization policy changes in Canada, while ACF is more useful for understanding the belief systems of different interest groups and the conflicts and interactions between coalitions. Two theoretical frameworks provide a comprehensive perspective on the complex policy process behind Canada's drug decriminalization policy.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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 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".