Examining the Politics behind Secondary Suites in Calgary
Bibliographic record
Abstract
Rolled as an election promise by Mayor Naheed Nenshi, secondary suites have gone from being the best idea among 12 Smart Ideas of Mayor Nenshi for Calgary, to being an issue, that has seen a long, tiring tug-of-war between Councillors every time it was on table for a vote, but always resulted in a stalemate. Both sides of the argument have their own reasons for voicing for or against allowing city-wide secondary suites. With around 50% of the Calgary City Council’s time spent on debating upon the homeowner’s applications for secondary suites in single family dwelling units, the policy paralysis continues to exist. The issue has been procrastinated to be discussed around the next municipal elections in 2017. While the tight rental market keeps widening the gap between demand and supply of affordable housing, status quo on secondary suites has only worsened the situation of housing in Calgary. In this paper, we begin by stating the land-use regulations that guide the zoning of Calgary city, provincial regulations that govern the building types in Calgary and then state the arguments of those for and against secondary suites based on the issues of land use and building codes. We provide a theoretical base to the politics of land use by relating the problem to the Home Voter Hypothesis of William Fischel and examine the viewpoint of City Councillors in the light of the theory. We then suggest various remedies to overcome the political stalemate on secondary suites using the Median Voter Theorem, and learning from various cities that have successfully implemented the idea in Canada.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.016 | 0.012 |
| Scholarly communication | 0.009 | 0.001 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.012 | 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".