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Record W1993694832 · doi:10.1080/14797585.2013.851834

Performing the limits of finance

2013· article· en· W1993694832 on OpenAlexaff
Rob Aitken

Bibliographic record

VenueJournal for Cultural Research · 2013
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicHousing, Finance, and Neoliberalism
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsExpansiveFinanceTechnocracyImpossibilityAbstractionFaithEconomicsSociologyEpistemologyPolitical scienceLawPhilosophy

Abstract

fetched live from OpenAlex

Recent financial turmoil has put emphasis once again on the very meaning and reach of ‘finance’. In doing so, recent financial crises have also provoked questions about the very ‘ends’ of finance: Where are the borders of finance? Given the expansive reach of financial innovation over the past two decades, are there any serious limits to the kinds of practices that can be converted into financial objects? Does the culture of finance (expansive and all encompassing) encounter meaningful interruptions? This paper explores these questions by reviewing a cluster of public-art responses to the 2008 financial crisis mounted by artists critical of the expansive logic of financial abstraction. This paper pays particular attention to the work of Fergal McCarthy and Fred Forest, two public artists who have confronted finance and its rational culture with practices of gameplay, whimsy, and carnival. In doing so, these artists invoke a strategy designed to lay the all-encompassing claims of financial abstraction alongside its own impossibility; alongside performances which undermine the expansive claims of financial abstraction. These are strategies, I conclude, which can interrupt the technocratic discourses which dominate the contemporary cultures of finance; strategies which, in the words of one artist, evoke ‘plausible states of uncertainty’ about our faith in financial abstraction.

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)0.002
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.703
Threshold uncertainty score0.527

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
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 head0.215
GPT teacher head0.375
Teacher spread0.160 · 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

Citations2
Published2013
Admission routes1
Has abstractyes

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