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Record W2529795368 · doi:10.24926/265535.994

Too Big to Fool: Moral Hazard, Bailouts, and Corporate Responsibility

2017· article· en· W2529795368 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueMinnesota law review · 2017
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicGlobal Financial Regulation and Crises
Canadian institutionsCentre for International Governance Innovation
Fundersnot available
KeywordsMoral hazardToo big to failCorporate governanceBusinessSystemic riskExternalityIncentiveLaw and economicsBailoutFinancial crisisGovernment (linguistics)FinanceEconomicsMarket economyMicroeconomics

Abstract

fetched live from OpenAlex

2. The acronym TBTF is sometimes used as an adjective by referring to systemically important financial firms as TBTF firms.For clarity, this Article hereinafter refers to these firms as simply systemically important firms.3. Although TBTF has also been described as a problem of taxpayerfunded government bailouts, that description is partly circular.A systemically important firm would only need a bailout to avoid failure, and failure would most likely result from excessive risk-taking.If that risk-taking could be controlled, the need for government bailouts would be greatly reduced.Part IV.A of this Article examines how to control that risk-taking.Part IV.B of the Article examines how to minimize the public cost of bailing out systemically important firms that would fail notwithstanding that risk-taking control.See infra

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.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.897
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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)0.0000.001

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 head0.132
GPT teacher head0.283
Teacher spread0.151 · 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