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Record W3001271888 · doi:10.1177/0042098019895226

A regional growth ecology, a great wall of capital and a metropolitan housing market

2020· article· en· W3001271888 on OpenAlexaffabout
David Ley

Bibliographic record

VenueUrban Studies · 2020
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicHousing, Finance, and Neoliberalism
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsReal estateDeregulationEconomicsMetropolitan areaImmigrationCapital (architecture)EconomyGlobalizationGovernment (linguistics)FinanceMarket economyPolitical scienceGeography

Abstract

fetched live from OpenAlex

In a narrative framed by Harvey Molotch’s growth machine thesis, this article examines the globalisation of property in gateway cities, and its contribution to house price inflation in Vancouver, the least affordable market in North America. In response to a floundering British Columbia (BC) economy, a favourable investment and immigration climate welcomed capital and invited capitalists to re-locate their economic skills. Substantial funds flowed to Vancouver from the buoyant Asia Pacific, from distant investors and wealthy immigrants. Capital flows were facilitated by a powerful growth coalition, as the provincial government benefited significantly from these funds, and held a common interest with a vigorous trans-Pacific property industry. Supporting this growth coalition, the deregulation of private institutions and the under-resourcing of public agencies working in the capital/real estate nexus provided an ecology favourable to the ‘animal spirits’ of the market, including real estate opportunism and money laundering. Such a growth ecology, exacerbating severe unaffordability, may exist in other globally networked cities, though relations are rarely so well developed and so powerful in their effects.

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)0.000
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 score0.319
Threshold uncertainty score0.707

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.051
GPT teacher head0.232
Teacher spread0.181 · 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

Citations28
Published2020
Admission routes2
Has abstractyes

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