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The Financialization of Urban Redevelopment

2010· article· en· W2112225368 on OpenAlexaffabout
Ted Rutland

Bibliographic record

VenueGeography Compass · 2010
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicHousing, Finance, and Neoliberalism
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsFinancializationRedevelopmentDowntownAsset (computer security)Capital (architecture)SociologyEconomicsFinancePolitical sciencePolitical economyEconomyHistoryLaw

Abstract

fetched live from OpenAlex

Abstract Spurred by the conviction that not only financial capital but also changes in finance and changes in its relations with non‐financial activities have immense and complicated consequences for ongoing processes of urban redevelopment, this article puts the presently separate financialization and urban redevelopment literatures in conversation. The article begins with a review of the financialization literature, outlining and evaluating four different approaches to the topic and seeking to consider what, if anything, they might have to offer to an area of inquiry that has long considered finance to be a central concern. The second section examines how financial capital has been analyzed in the urban redevelopment literature since the pioneering work of David Harvey in the 1970s. The final section examines how financialization has played out in the medium‐sized port city of Halifax, Nova Scotia. Drawing on interviews with financiers and property developments, as well as secondary research materials, the study describes how a recent urban design process in Halifax enlisted urban images and ideas to rewrite development regulations, eliminate popular political involvement in the development approvals process, and lever open the downtown landscape to the whims of worldwide financial markets. The essay concludes that studies of urban redevelopment would indeed gain something by engaging with the financialization literature, so long as the former continue to attend not just to financial capital but also to the material and ideological mechanisms through which property is continually reproduced as a financial asset.

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: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.075
Threshold uncertainty score0.149

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 studies0.0040.011
Scholarly communication0.0040.001
Open science0.0010.003
Research integrity0.0000.001
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 head0.013
GPT teacher head0.198
Teacher spread0.185 · 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 designQualitative
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

Citations138
Published2010
Admission routes2
Has abstractyes

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