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Record W4304812164 · doi:10.1177/27541258221130327

The moral rent gap: Views from an edge of an urban world

2022· article· en· W4304812164 on OpenAlexaff
Elvin Wyly

Bibliographic record

VenueDialogues in Urban Research · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicUrban Planning and Governance
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsContext (archaeology)OutrageGentrificationSpace (punctuation)SociologyEconomic rentEconomicsLaw and economicsPolitical scienceGeographyLawEconomic growthMicroeconomics

Abstract

fetched live from OpenAlex

For more than 40 years, Neil Smith's rent gap theory of gentrification has been one of the most influential concepts in critical urban research. In recent years, however, the rent gap has been challenged as an economically deterministic tool suitable only for the study of inner city land parcels in certain types of deindustrializing cities of the Global North. But what if the rent gap was never really about economics, but instead about moral outrage? And what happens when moral and ethical questions about access to urban space are extended across multiple human generations? This article develops the concept of the moral rent gap: juxtapositions, tensions, and often irreconcilable contradictions in the present use of urban land in the context of intergenerational debts and responsibilities. Parcels of urban land are not clear, Cartesian locations, but are portals into multidimensional transformations of space and time produced through diverse, competing moral claims to the benefits of urban life.

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)0.005
metaresearch head score (Gemma)0.005
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: none
Teacher disagreement score0.012
Threshold uncertainty score0.059

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.001
Science and technology studies0.0110.061
Scholarly communication0.0120.016
Open science0.0010.010
Research integrity0.0040.008
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 head0.251
GPT teacher head0.430
Teacher spread0.179 · 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

Citations14
Published2022
Admission routes1
Has abstractyes

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