MétaCan
Menu
Back to cohort
Record W4319662209 · doi:10.58840/ots.v2i1.8

Canadian Real Estate and Financial Geographies

2023· article· en· W4319662209 on OpenAlexaboutno aff
Denis Kartal

Bibliographic record

VenueOTS Canadian Journal · 2023
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicHousing, Finance, and Neoliberalism
Canadian institutionsnot available
Fundersnot available
KeywordsFinanceRentingEconomicsCapital marketFinancial crisisReal estateContext (archaeology)Financial marketPolitical scienceMacroeconomics

Abstract

fetched live from OpenAlex

This article is about new governments for financial recovery after the financial crisis. The focus on tracing the creation of an active class derived from the security of rental income for detached houses has become rent. The study strategically combines conceptual agendas, and is discussed separately. Market formation theories rooted in scientific and technical studies provide information on the analytical method to pay attention to the work of realizing markets, the role of computer devices in market formation and the conditional and conditional aspects of markets. This analysis shows that renting families in an active class is a practical achievement. However, a broader framework rooted in the political economy is needed to address the broader meaning of the working class in terms of power, politics and the dynamics of capital accumulation. The article focuses in particular on the historical and geographical events that make it possible to invent a large-scale SFR market, the work of state and capital market players to reformulate single-family homes restored as rental properties, and the role of accounting practices in this process, and the strategies of issuers and credit rating agencies to develop a new asset class for institutional investors. The working-class points to the fundamental role for housing in the ideology of capital, and talks about new implications of financial role players and domestic life, as financial accumulation adapts to the context after the crisis. In addition to the financial financing of housing after the crisis, the article also shows how economic geographers can carefully integrate the theoretical perspectives to critically examine the conditions of market formation and the social, spatial and political consequences of markets.
 

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.531
Threshold uncertainty score0.771

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0010.000
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 head0.017
GPT teacher head0.190
Teacher spread0.173 · 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

Citations0
Published2023
Admission routes1
Has abstractyes

Explore more

Same venueOTS Canadian JournalSame topicHousing, Finance, and NeoliberalismFrench-language works237,207