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Record W2085763257 · doi:10.1068/a130226p

The political economy of mortgage securitization and the neoliberalization of housing policy in Canada

2015· article· en· W2085763257 on OpenAlexaffabout
Alan Walks, Brian Keith Clifford

Bibliographic record

VenueEnvironment and Planning A Economy and Space · 2015
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicHousing, Finance, and Neoliberalism
Canadian institutionsSimon Fraser UniversityUniversity of Toronto
Fundersnot available
KeywordsSecuritizationFinancializationSecondary mortgage marketFinancial systemMarket economyRentingBusinessSolvencyCapitalismPoliticsEconomicsFinanceMortgage insuranceMarket liquidityPolitical scienceInsurance policy

Abstract

fetched live from OpenAlex

The Canadian case represents a distinct variety of financialization under capitalism, one conditioned by the structure of its mortgage markets and the dominant role played by the state in the process of mortgage securitization. Securitization has been a key component of the neoliberalization of housing policy, with new state roles in the insuring, directing and funding of residential mortgage-backed securities both undergirding and justifying the federal shift from the provision of social rental housing toward supporting a rental market increasingly characterized by private sector individualunit landlord-investors. It was primarily the state's control over, and utilization of, the securitization process that maintained the solvency of the financial system in the face of the global financial crisis. However the resulting rapid uptake of liabilities on behalf of both the state and households brought forth new contradictions, necessitating new policy experimentation and reregulation, to which securitization was once again directed and which now articulate the political economy of housing in the country.

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)0.001
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.228
Threshold uncertainty score0.896

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0120.008
Scholarly communication0.0060.001
Open science0.0010.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0040.000

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 head0.015
GPT teacher head0.193
Teacher spread0.177 · 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 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

Citations91
Published2015
Admission routes2
Has abstractyes

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