Not on My Main Street: Zoning Marijuana Prohibition and the municipal theatre of the War on Drugs
Bibliographic record
Abstract
This thesis examined the development and application of urban bylaws, in this case the City of Delta’s, which regulate properties commonly hosting growing operations or laboratories producing and handling federally-listed controlled substances such as marijuana. The project was largely exploratory and involved qualitative examination public documents such as council meetings, reports, memos and correspondence regarding Delta’s Zoning Bylaw and Controlled Substance Property Bylaw—which control how land and property are used in the municipality and impose punitive sanctions on owners and renters who infract on these regulations. Prohibitionist bylaws such as these can have disruptive consequences on the national legalization of marijuana due to these bylaws de facto continuing prohibition on the local level. The project uncovered justifications behind the ordinance—both formal and informal—and found a legal ecosystem of related municipal ordinances interacting with the (specifically those involved with medical marijuana dispensaries and production facilities), potential overlaps between bylaws as a result of higher-level changes in law as well as legal and economic consequences—such as creating favourable conditions for large agribusiness. Keywords:
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.012 | 0.012 |
| Scholarly communication | 0.008 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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".