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Record W2126246517 · doi:10.1068/d13165p

Capital Fixity and Mobility in Response to the 2008–09 Crisis: Variegated Neoliberalism in Mexico and Turkey

2014· article· en· W2126246517 on OpenAlexaff
Hepzibah Muñoz Martínez, Thomas Marois

Bibliographic record

VenueEnvironment and Planning D Society and Space · 2014
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicHousing, Finance, and Neoliberalism
Canadian institutionsUniversity of New Brunswick
Fundersnot available
KeywordsNeoliberalism (international relations)State (computer science)Capital (architecture)MaterialismFinancial crisisFinancializationPolitical economyCapital accumulationInvestment (military)Political scienceDevelopment economicsEconomicsEconomyEconomic systemMarket economyHuman capitalGeographyKeynesian economicsLaw

Abstract

fetched live from OpenAlex

This paper examines the responses to the 2008–09 global financial crisis in Mexico and Turkey as examples of variegated neoliberalism. The simultaneous interests of corporations and banks in the national fixing of capital and their mobility in the form of global investment heavily influenced these states' policy responses to the crisis at the expense of the interests of the poor, workers, and peasantry. Rather than pitching this as evidence of either persistent national differentiation or some Keynesian state resurgence, we argue from a historical materialist geographical framework that the responses of capital and state authorities in Mexico and Turkey actively constitute and reconstitute the global parameters of market regulatory design and neoliberal class rule through each state's distinct domestic policy formation and crisis management processes. The latter is influenced by capitalists' ties to the fixity and motion of capital. While differing in specific content, the form of Mexico's and Turkey's official responses to the crisis ensured continuity in their neoliberal strategies of development and capital accumulation.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.186
Threshold uncertainty score0.654

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 head0.013
GPT teacher head0.199
Teacher spread0.186 · 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 designObservational
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

Citations18
Published2014
Admission routes1
Has abstractyes

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