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Record W3039036115 · doi:10.1080/09692290.2020.1788114

What finance wants: explaining change in private regulatory preferences toward sovereign debt restructuring

2020· article· en· W3039036115 on OpenAlexaff
Skylar Brooks

Bibliographic record

VenueReview of International Political Economy · 2020
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicGlobal Financial Regulation and Crises
Canadian institutionsBank of Canada
Fundersnot available
KeywordsRestructuringCreditorPreferenceEconomicsSovereigntyArgument (complex analysis)PoliticsDebtDebt restructuringLaw and economicsSovereign debtPolitical scienceFinanceLawMicroeconomics

Abstract

fetched live from OpenAlex

It is widely assumed that when private financial actors seek to influence the regulation of global finance, their preference is for fewer or weaker rules. But is this preference tied to fixed material interests, or is it more malleable? Can it change over time? If so, why might it? I address these questions by examining a recent shift in private creditor preferences toward the regulation of sovereign debt restructuring. I argue that changed material circumstances created demand for regulatory change among creditors but did not determine the nature of their preferred solution. Instead, it was shifts in collectively-held ideas—the specific content of which was informed by important historical and contextual factors—that led private creditors to embrace stronger debt restructuring rules, despite being historically opposed to such rules. In making this argument, the article contributes to a fuller understanding of private market actors in global financial politics, challenging the assumption that these actors necessarily prefer weaker rules, and highlighting the more contingent nature of their regulatory preferences. It also contributes to wider debates about preference formation and change, highlighting important complementarities between distinct theoretical traditions, which together provide a much richer explanation of the case at hand.

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)0.009
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.019

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.005
Scholarly communication0.0030.003
Open science0.0000.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0040.000

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 head0.080
GPT teacher head0.291
Teacher spread0.210 · 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 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

Citations2
Published2020
Admission routes1
Has abstractyes

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