Zoned in: The Influence of Land Use Policy on Canadian Craft Breweries
Bibliographic record
Abstract
ABSTRACT Municipal zoning bylaws have a considerable effect on the micro‐geographies of craft brewing. This paper examines the location of craft breweries across Canada and provides an analysis of how land use policy delineates the spatial location of craft breweries in six Canadian cities. Using the parcel level location of breweries as an entry point, our findings confirm how zoning bylaws have broadened the spatial parameters of brewing operations beyond industrial zones. However, while breweries are permitted/discretionary across a wider range of land uses, there is still a concentration of breweries around downtown, industrial, and special districts. Breweries remain largely prohibited from residential zones, part of a broader process of restricting any form of commercial and/or industrial use in single family zones. Our findings link with existing research on the locational dynamics of breweries. While the spatial parameters for zoning were recently broadened, most municipal standards collapse differences across breweries pertaining to orientation (production/consumption) and/or size of facility/output. Our research shows that, in these six cities, the potential for placemaking now extends beyond post‐industrial sites. We argue that municipalities should implement further regulatory measures to ensure compatibility between uses, by differentiating breweries according to their orientation and scale.
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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 | 0.001 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 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".