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Record W3215233281 · doi:10.1111/anti.12795

Securitising Seniors Housing: The Financialisation of Real Estate and Social Reproduction in Retirement and Long‐Term Care Homes

2021· article· en· W3215233281 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueAntipode · 2021
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicHousing, Finance, and Neoliberalism
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsRestructuringReal estateBusinessRevenueFinanceLabour economicsHospitalityWelfareEconomic rentEquity (law)EconomicsMarket economy

Abstract

fetched live from OpenAlex

Abstract The financialisation of seniors housing has reshaped Canadian long‐term care homes (LTCs) and retirement communities since the 1990s. Investors have flocked to profit from the demographic “grey wave” driving demand. Financialised firms (private equity, institutions, publicly listed companies, and real estate investment trusts) have consolidated ownership of 33% of seniors housing (22% and 42% of LTCs and retirement homes). Facilitated by neoliberal healthcare reforms, welfare state restructuring, and the privatisation of social reproduction, the business strategies of financial firms rely on the dual nature of seniors housing as both (1) real estate, and (2) an operating business (delivering hospitality and healthcare services). As real estate, firms profit from repositioning properties and by raising rents. As an operating business, firms raise revenues by adding on escalating private‐pay healthcare and hospitality fees over time; and cut expenses by extracting more value from the socially reproductive labour of care workers, who are largely precariously employed, racialised women.

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.

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 score0.206
Threshold uncertainty score0.395

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0000.000

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 head0.024
GPT teacher head0.240
Teacher spread0.216 · 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