Longing for Effective Short-Term Rental Regulation: How Cities Are Responding and What Is the Appropriate Course of Action for Toronto
Bibliographic record
Abstract
The rise of the sharing and digital economies have resulted in the excessive growth of the short-term rental markets in most parts of the world, impacting urban tourism and its related influences on livability in urban centres. The study examined the impacts short-term rentals have on both securing adequate and affordable housing in urban landscapes while considering the socio-spatial externalities created by this inherent form of usage. As the city of Toronto continues to experience excessive growth of this market segment, the study aimed to explore nuanced policy in three international cities which experience similar patterns and challenges present in Toronto. The recommendations set forth in this report are targeted to municipal planners, city staff, and politicians to reconsider and apply targeted policy to address current regulatory and enforcement shortfalls, while developing regulatory schemes that adapt to changing market conditions. By employing policy interventions best suited for their unique urban environment and conditions, the city of Toronto can further advance and control the externalities emanating from short-term rentals.
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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 | 0.005 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.014 | 0.014 |
| Scholarly communication | 0.015 | 0.005 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.004 | 0.004 |
| 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".