Displacement by disruption: short-term rentals and the political economy of “belonging anywhere” in Toronto
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Using data from the consulting firm Airdna, I map Airbnb listing activity in the City of Toronto between June 2016 to May 2017 to assess claims that short-term rental platforms might be implicated in displacing local renter communities. I find that the majority of Airbnb’s revenue within the city derives from full-time, commercially-oriented hosts operating in select downtown neighbourhoods, noting that these findings run up against discourses of sharing and belonging frequently advanced by sharing economy platforms like Airbnb. Instead, I argue the platform creates significant incentives for investors and landlords to pursue greater rental profits in the tourism market where they might otherwise house stable, local tenants. I conclude by discussing how an expanding and digitalized short-term rental industry is now both a symptom and driver of processes of gentrification and socio-spatial polarization in contemporary cities, contextualizing its emergence as part of a broader trend towards the financialization of housing.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it