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Record W2213746620 · doi:10.3138/cras.2015.s09

Archiving the Rust Belt: Investigating Rust Belt Narratives of American Exceptionalism through Buffalo’s Downtown Department Store

2015· article· en· W2213746620 on OpenAlexfundvenueno aff
Patrick Manning

Bibliographic record

VenueCanadian Review of American Studies · 2015
Typearticle
Languageen
FieldArts and Humanities
TopicArt History and Market Analysis
Canadian institutionsnot available
FundersMcMaster University
KeywordsExceptionalismAmerican exceptionalismCityscapeNarrativeGentrificationRust (programming language)SynecdocheDowntownInequalitySociologyParadePolitical scienceHistoryLawArtArchaeologyMetaphorVisual artsEconomicsLiteratureEconomic growthMetonymyPolitics

Abstract

fetched live from OpenAlex

In this article, Buffalo’s now defunct flagship department store Adam, Meldrum & Anderson is discussed as a synecdoche for broader concerns facing the Rust Belt region, including gentrification, de-industrialization, urban renewal, and systemic inequality. Through an intersection of archival theory and the discourses of American exceptionalism, it is argued that the Rust Belt’s economic downfalls have been recreated as capitalist opportunities, a process that obfuscates economic inequality. To demonstrate the disruptive potential of the archive, an archived photograph is analysed alongside Dennis Maher’s reimagining of Buffalo’s cityscape. Ultimately, these alternative imaginings work toward a more equitable Rust Belt landscape.

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)0.004
metaresearch head score (Gemma)0.006
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: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.087
Threshold uncertainty score0.174

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.004
Science and technology studies0.0280.033
Scholarly communication0.0130.008
Open science0.0020.008
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0070.000

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 head0.082
GPT teacher head0.307
Teacher spread0.225 · 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

Citations1
Published2015
Admission routes2
Has abstractyes

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