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Record W2989750926 · doi:10.1177/0308518x19884577

Making a market for itself: The emergent financialization of student housing in Canada

2019· article· en· W2989750926 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueEnvironment and Planning A Economy and Space · 2019
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicHousing, Finance, and Neoliberalism
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsFinancializationReal estateReal estate investment trustInvestment (military)FinanceAccommodationPhenomenonBusinessEconomicsEconomic geographyPolitical science

Abstract

fetched live from OpenAlex

This paper demonstrates the infiltration of finance into increasingly niche real estate sectors, taking the example of the emergent Canadian purpose-built student accommodation (PBSA) sector since 2011. Drawing on a novel database of PBSA, qualitative document analysis, and key informant interviews, we uncover the business strategies and geographic patterns of investment in the sector. We then consider the local impacts of this phenomenon in Waterloo, Ontario, the country’s largest PBSA market, where finance-driven new-build studentification has contributed to higher housing costs and age segregation. This process of financialization has differed from other housing sectors as it depends on the creation of new student housing to provide an avenue for investment therein. At the same time, finance-driven new-build studentification functions as a spatial fix by directing investment to secondary cities. However, this process has been fragile, marked as much by failure as success, pointing to the limits of financialization.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.374
Threshold uncertainty score0.986

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.024
GPT teacher head0.211
Teacher spread0.187 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it