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Record W4416926557 · doi:10.36939/cjur/vol31no1/art391

Modal logics of aging purpose-built rental housing in Vancouver’s suburbs

2022· article· W4416926557 on OpenAlexafffundvenueabout
Colin Jones

Bibliographic record

VenueCanadian journal of urban research · 2022
Typearticle
Language
FieldEconomics, Econometrics and Finance
TopicHousing, Finance, and Neoliberalism
Canadian institutionsUniversity of British Columbia
FundersSocial Sciences and Humanities Research Council of CanadaReal Estate Foundation of British Columbia
KeywordsRedevelopmentRentingStock (firearms)Rental housingDemolitionReal estateAffordable housingEconomic shortage

Abstract

fetched live from OpenAlex

Most Vancouver’s suburban stock of purpose-built rental housing is aging, and there is concern that much of it could soon face redevelopment pressure. Previous research has demonstrated the importance of this stock for providing marginalized renters with naturally occurring affordable housing options, and the displacement of renters for redevelopment has been observed in certain Metro Vancouver neighbourhoods. Further, there is a shortage of affordable rental housing options in suburban Vancouver, which may be exacerbated by the demolition of the older stock. In late-2016 to early-2017 I conducted 27 semi-structured interviews with urban planners, politicians, real estate and housing professionals to collect a range of perspectives on the past, present and future of aging rental housing in Vancouver’s suburbs. The key insights to emerge from this research are that the current rental stock is insufficient to meet demand, government policy may have contributed to a lack of supply, and expanding the supply of suburban rental housing will depend on maintaining a delicate balance between preservation and redevelopment.

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)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.328
Threshold uncertainty score0.660

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0080.010
Scholarly communication0.0050.001
Open science0.0010.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.000

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 head0.097
GPT teacher head0.288
Teacher spread0.192 · 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 designTheoretical or conceptual
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

Citations1
Published2022
Admission routes4
Has abstractyes

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