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Record W3202402752 · doi:10.2148/benv.47.3.355

Contagion in the Markets? Covid-19 and Housing in the Greater Toronto Area

2021· article· en· W3202402752 on OpenAlexaboutno aff
Murat Üçoğlu, Roger Keil, Seyfi Tomar

Bibliographic record

VenueBuilt Environment · 2021
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicHousing Market and Economics
Canadian institutionsnot available
Fundersnot available
KeywordsSuburbanizationCoronavirus disease 2019 (COVID-19)FinancializationAffordable housingConvergence (economics)PandemicEconomicsFinancial crisisEconomic geographyEconomic growthGeographyMarket economyMacroeconomics

Abstract

fetched live from OpenAlex

The Covid-19 pandemic has had crucial impacts on housing markets as working from home has become a new normal for certain economic groups. In this paper, we analyse the specific role the pandemic played in worsening the ongoing housing affordability crisis in the Greater Toronto Area (GTA). The GTA has, in fact, been experiencing a housing crisis since the early 2000s. In this paper, we argue that this continuing affordability crisis stems from the economic growth model that was embraced in the late 1990s, and we discuss why the existing market-oriented housing model has failed. The economic growth model of the Toronto region depends on the convergence of the financialization of housing and massive suburbanization. Because of this, the new wave of suburbanization that has accelerated with the outbreak of Covid-19 is not a new phenomenon for the GTA. In the final analysis, we also illustrate that the ongoing Covid-related-suburbanization in the GTA has deepened the housing crisis as the region continues to be less and less affordable.

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.

How this classification was reachedexpand

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)0.001
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 score0.281
Threshold uncertainty score0.671

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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)0.0010.000

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 head0.045
GPT teacher head0.220
Teacher spread0.175 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations9
Published2021
Admission routes1
Has abstractyes

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