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Regul(ariz)ation of Fringe Credit: Payday Lending and the Borders of Global Financial Practice

2010· article· en· W1977865032 on OpenAlexaff
Rob Aitken

Bibliographic record

VenueCompetition & Change · 2010
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicHousing, Finance, and Neoliberalism
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsCorporate governanceContext (archaeology)PerformativityGlobalizationFinancial crisisArgument (complex analysis)Set (abstract data type)Object (grammar)SociologyEconomicsFinancePolitical economyBusinessPolitical scienceMarket economyMacroeconomicsLinguisticsComputer scienceHistory

Abstract

fetched live from OpenAlex

The recent financial crisis has been punctuated by a discussion of the future of global financial governance in terms of a ‘regulation/deregulation’ formula. This paper argues for a broadening of this frame by taking seriously recent claims of performativity. To place changes associated with financial globalization in a more complicated critical context, this paper explores the ways in which global finance has often entailed a redrawing of the boundaries between the financial and the everyday. To develop this argument, the paper focuses, in particular, on practices of payday lending and on recent regulatory changes which have performed payday lending in a particular set of ways. Reading payday lending as both a repertoire of market devices and a set of dividing practices, this paper concludes that regulation performs the object it seeks to manage by invoking ambiguous, and not singular, territories of governance.

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)0.008
metaresearch head score (Gemma)0.008
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.009
Threshold uncertainty score0.041

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0040.046
Scholarly communication0.0090.005
Open science0.0010.006
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 head0.031
GPT teacher head0.250
Teacher spread0.219 · 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

Citations18
Published2010
Admission routes1
Has abstractyes

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