MétaCan
Menu
Back to cohort

<scp>F</scp>rance and the International Financial Crisis: The Legacy of State‐Led Finance

2012· article· en· W2129029723 on OpenAlexaboutno aff
David Howarth

Bibliographic record

VenueGovernance · 2012
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicGlobal Financial Crisis and Policies
Canadian institutionsnot available
Fundersnot available
KeywordsSecuritizationFinancial systemFinancial crisisState (computer science)LiberalizationBusinessFinancial regulationQuarter (Canadian coin)Money marketFinanceEconomicsMarket economyInterest rate

Abstract

fetched live from OpenAlex

Despite the far‐reaching liberalization of theFrench banking system over the past quarter century,French banks suffered far less in the international financial crisis (2007–2009) than banks in theUnitedKingdom andGermany. However, theFrench system also suffered far more—at least in the first stages of the crisis—than the banking systems ofSouthernEurope. By several measures,French banks were world leaders in financial innovation, and theFrench banking system was highly exposed to international market movements. The limited impact of the crisis, however, owed to the specificities ofFrench “market‐based banking.” Deliberate state action over the two decades prior to the crisis created a specific kind of banking system and encouraged forms of financial innovation, the unintentional consequence of which was the limited exposure to the securitization that caused the damage wrought during the financial crisis.

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)0.001
metaresearch head score (Gemma)0.003
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: none
Teacher disagreement score0.032
Threshold uncertainty score0.064

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0020.003
Scholarly communication0.0070.004
Open science0.0000.002
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.0140.001

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 head0.012
GPT teacher head0.206
Teacher spread0.195 · 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

Citations32
Published2012
Admission routes1
Has abstractyes

Explore more

Same venueGovernanceSame topicGlobal Financial Crisis and PoliciesFrench-language works237,207