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Record W4383551408 · doi:10.1002/9781119853619.ch5

Vancouver

2023· other· en· W4383551408 on OpenAlexaboutno aff

Bibliographic record

Venuenot available
Typeother
Languageen
FieldEconomics, Econometrics and Finance
TopicHousing, Finance, and Neoliberalism
Canadian institutionsnot available
Fundersnot available
KeywordsInvestment (military)PoliticsCapital (architecture)ImmigrationState (computer science)Market economyEconomicsEconomyBusinessEconomic policyPolitical scienceGeography

Abstract

fetched live from OpenAlex

This chapter examines attempts to reregulate a housing market made dysfunctional by the incessant flow of investment capital, the marketisation of state policy within a neoliberal regime, and the power of a property-based growth coalition. Substantial golden visa immigration and offshore buyers established a strong transnational residential sales network between Vancouver and East Asia after 1986, adding significant speculative investment to local demand. By 2016, any homeownership aspiration had reached a dead end for many residents. After a renewed investment surge (like Sydney's) from 2013-16, affordability became a serious local irritant and led (unlike Sydney) to political reversals in regional and federal elections. Newly-elected governments with housing strategies to reregulate the market introduced taxation-driven cooling of surplus demand, especially from overseas, and revived construction and renovation of social housing. A well-endowed National Housing Strategy was launched. But the deregulated past leaves a heavy legacy that cannot easily be corrected.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.939
Threshold uncertainty score0.000

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.000
Scholarly communication0.0040.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.5570.249

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 head0.027
GPT teacher head0.214
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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreOther

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

Citations0
Published2023
Admission routes1
Has abstractyes

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