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Record W2525467847 · doi:10.1177/1527476416667821

Social Mobility: Charting the Economic Topography of Urban Space

2016· article· en· W2525467847 on OpenAlexafffundabout
Heather Zwicker, Kisha Supernant, Erika Luckert

Bibliographic record

VenueTelevision & New Media · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicUrban Planning and Governance
Canadian institutionsUniversity of Alberta
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsGentrificationCapitalismColonialismSpace (punctuation)SociologyThematic mapLiteral (mathematical logic)Late capitalismUrban spacePoetryAestheticsMedia studiesEconomic geographyGeographyCartographyPoliticsRegional sciencePolitical scienceComputer scienceArtArchaeologyCivil engineeringLawLiteratureEngineering

Abstract

fetched live from OpenAlex

This project on economic topographies is one of eight thematic ways in which the research group Edmonton Pipelines is remapping the neighborhood of Rossdale. The essay brings together poetry, data visualization, and technologies of mapping to analyze how the twin vectors of capitalism and colonialism have created Western Canadian cityspace. Rather than taking for granted the ups and downs of the built environment, the article muses on the possibilities of using haunting as an urban interface. Working through this metaphorical possibility concretely, this essay traces the contours of haunting in the case of Rossdale, a Canadian neighborhood that has undergone an emblematic form of gentrification. We develop literal topographical maps as a way of conceptualizing metaphorical hurdles to belonging to settler colonial cities. These socioeconomic topographical maps serve as a new form of urban cartography.

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)0.001
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: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.371
Threshold uncertainty score0.347

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
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 head0.030
GPT teacher head0.288
Teacher spread0.258 · 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 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

Citations1
Published2016
Admission routes3
Has abstractyes

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