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Record W2969754836 · doi:10.1080/02673037.2019.1646217

Condominium self-governance? Issues, external interests, and the limits of statutory reform

2019· article· en· W2969754836 on OpenAlexaffabout
Stefan Treffers, Randy K. Lippert

Bibliographic record

VenueHousing Studies · 2019
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicHousing, Finance, and Neoliberalism
Canadian institutionsUniversity of WindsorYork University
Fundersnot available
KeywordsStatutory lawStatuteCorporate governanceState (computer science)Self-governancePublic administrationPolitical scienceLawBusinessFinance

Abstract

fetched live from OpenAlex

Condominiums are assumed in enabling statutes, related regulations, and statutory reforms to resemble ‘self-governing communities’ of owners whom collectively undertake numerous governance responsibilities to manage and sustain their buildings and living arrangements. Drawing from intensive interviews with condo owners and condo industry representatives in Ontario and New York State and a large qualitative survey of condo owners from Ontario, we outline five overlapping and longstanding governance issues that challenge the notion of self-governance and reveal it to be more illusion than reality. This disjuncture stems not only from common dilemmas of collective governance, but also from the growing influence of external and mostly commercial interests in condominiums broadly consistent with neo-liberalization. We also consider more recent reform attempts by Ontario and New York State and discuss statutory limitations in addressing these issues. We express doubt that condo statutory reform alone can successfully remedy the governance problems facing condo housing and proffer remedies including moving beyond the perception of condominiums as autonomous, self-governing realms.

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)0.007
metaresearch head score (Gemma)0.013
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.292
Threshold uncertainty score0.581

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.013
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0040.025
Scholarly communication0.0050.004
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.036
GPT teacher head0.262
Teacher spread0.226 · 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
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

Citations24
Published2019
Admission routes2
Has abstractyes

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