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Cool Canada: A Case of Low Market-Based Banking in the Anglo-Saxon World

2013· book-chapter· en· W2503931547 on OpenAlexaboutno aff
Patrick Leblond

Bibliographic record

VenueOxford University Press eBooks · 2013
Typebook-chapter
Languageen
FieldEconomics, Econometrics and Finance
TopicBanking stability, regulation, efficiency
Canadian institutionsnot available
Fundersnot available
KeywordsLeverage (statistics)Balance sheetAsset (computer security)Financial systemContext (archaeology)BusinessRetail bankingLiabilityFinancial crisisCapital marketMarket shareCompetition (biology)Government (linguistics)Monetary economicsMarket economyEconomicsFinance

Abstract

fetched live from OpenAlex

Faced with the world’s worst financial crisis since the Great Depression, Canada remained an oasis of relative financial stability while Europe and the United States succumbed to the pressures of rapidly depreciating assets, indebtedness and frozen credit markets. In the context of this volume’s argument, the explanation for this admirable performance by the Canadian banking system rests squarely on its low exposure to market-based activities, both on the asset and liability sides of the balance sheet. Why does Canada have a banking system that is less market based than one might expect given its liberal market economy? The relatively low level of market-based banking in Canada is a result of, on the one hand, a concentrated banking sector protected from competition and, on the other hand, a relatively tougher regulatory system in terms of capital and leverage requirements. In making stability in the banking system a policy priority, the Canadian government ended up, more by accident rather than by design, slowing the growth of volatile market-based banking in Canada in favour of traditional banking activities that tend to be less risky in nature.

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)0.000
metaresearch head score (Gemma)0.001
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 score0.070
Threshold uncertainty score0.505

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.004
Science and technology studies0.0210.006
Scholarly communication0.0060.001
Open science0.0010.002
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.0050.000

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 head0.020
GPT teacher head0.178
Teacher spread0.158 · 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

Citations3
Published2013
Admission routes1
Has abstractyes

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