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Record W2336968863 · doi:10.1177/0964663915627492

Legal Knowledges and Surveillance in the Condo World

2016· article· en· W2336968863 on OpenAlexaffabout
Randy K. Lippert, Stefan Treffers

Bibliographic record

VenueSocial & Legal Studies · 2016
Typearticle
Languageen
FieldEnvironmental Science
TopicWildlife Conservation and Criminology Analyses
Canadian institutionsUniversity of Windsor
Fundersnot available
KeywordsStatuteCommodificationLawRealmCorporate governancePolitical scienceBusinessEconomicsFinanceEconomy

Abstract

fetched live from OpenAlex

This article explores legal knowledges and surveillance in residential condominiums, a form of property ownership and collective governing arrangement that is proliferating globally. Drawing from extensive empirical qualitative study of this realm in Toronto, Canada and New York, USA, including interviews with condo board members, owners and industry representatives, we map various legal knowledges and forms of surveillance and how these relate to condo governance and condo life. We demonstrate how surveillance is enabled by various legal knowledges flowing into the condo world, including those stemming from an evolving condo statute in the form of ‘counter-law’, but also from civil law, municipal law and criminal law. We show these legal knowledges have spawned video surveillance, key fobs, human surveillance, reserve fund studies, financial audits and safety inspections that together form a governing assemblage of private actors. This surveillance is largely focused on board and owners’ practices in relation to financial viability and property value, which has accompanied the condo becoming foremost an investment rather than a residential community. Much relevant legal knowledge and surveillance is increasingly commodified rather than developed or provided by the community, thus underscoring that the condo is an ever expanding conduit for the flow of such commodities. The article concludes with a discussion of several implications of this analysis, including the notion that the condo world may be experiencing a spiral of more and more law and surveillance.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.170
Threshold uncertainty score0.998

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 studies0.0000.001
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 head0.056
GPT teacher head0.323
Teacher spread0.267 · 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

Citations9
Published2016
Admission routes2
Has abstractyes

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