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Record W2344264231 · doi:10.1111/tesg.12184

Defiant Neoliberalism and the Danger of Detroit

2016· article· en· W2344264231 on OpenAlexaff
Jason Hackworth

Bibliographic record

VenueTijdschrift voor Economische en Sociale Geografie · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicUrban Planning and Governance
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsNeoliberalism (international relations)IdeologyNarrativeSociologySoftware deploymentPolitical economyPolitical scienceLawPoliticsPhilosophyEngineering

Abstract

fetched live from OpenAlex

Abstract Critical geographical studies of neoliberalism have emphasised how local spatialities complicate the implementation and theorisation of top‐down, idealised versions of the ideology. The central assumption is that local circumstances autonomously contradict or disrupt such deployments of neoliberalism. This paper explores the deployment of ‘defiant neoliberalism’, and the use of Detroit as a vehicle to promote and ‘prove’ its veracity. Some geographers have suggested that such defiant ideologies are unworthy of serious critique because they are so self‐evidently contradicted by local circumstances. The case calls into question the assumption that local circumstance naturally challenges ideological framings such as neoliberalism. Many local details contradict the veracity of idealised neoliberalism, yet its promoters are able to actively morph them (or elide them) into a narrative that supports the wider ideology.

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)0.007
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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.008
Threshold uncertainty score0.039

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0060.042
Scholarly communication0.0080.005
Open science0.0010.009
Research integrity0.0020.004
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 head0.007
GPT teacher head0.233
Teacher spread0.226 · 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 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

Citations8
Published2016
Admission routes1
Has abstractyes

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