Short-term rentals, long term consequences: regulation and enforcement of vacation rentals in small Canadian communities
Bibliographic record
Abstract
<p>The use of short-term vacation rental services has grown significantly since their establishment, but little concrete information is known about their effects on communities. The research that exists on the impacts of short-term rentals is heavily skewed toward larger cities and metropolitan areas, leaving smaller cities and rural areas unexamined. However, rural areas in Canada are experiencing faster growth of short-term rentals than urban areas. This study examines the regulations and enforcement regimes of three case study local governments across Canada, using interviews with planning professionals to consider the regulatory responses put forward by these communities and their perceived effects on STVR operations. Findings suggest that appropriate regulatory measures vary widely between communities. Recommendations are for those considering implementing STVR regulations, addressing housing protection, data gathering, and regulation typology.</p> <p><br></p> <p>Key words: short-term rental, regulation, enforcement, planning, small cities.</p>
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".