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Record W4247573139 · doi:10.5089/9781513527116.002

Canada

2020· article· en· W4247573139 on OpenAlexaboutno aff

Bibliographic record

VenueIMF Staff Country Reports · 2020
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicInsurance and Financial Risk Management
Canadian institutionsnot available
Fundersnot available
KeywordsBalance sheetBusinessContext (archaeology)Market liquidityFinancial crisisDeposit insuranceFinancial systemPensionFinancial stabilityFinanceEconomics

Abstract

fetched live from OpenAlex

This paper on Financial Safety Net and Crisis Management for the Canada reviews the stress testing and financial stability analysis. The paper highlights that the financial system’s performance has been strong. The insurance sector has remained financially sound even in the low interest rate environment. Major banks, life insurers, and pension funds have expanded their footprints abroad. Canada has strong financial linkages with the United States. Macrofinancial vulnerabilities—notably, elevated household indebtedness and housing market imbalances—remain substantial, posing financial stability concerns. Major deposit-taking institutions would be able to manage severe macrofinancial shocks; however, mortgage insurers would probably need additional capital. Major deposit-taking institutions also hold enough liquidity buffers to withstand sizeable funding outflows. However, increased balance sheet complexity and reliance on wholesale and foreign exchange funding, and the extensive use of derivatives are some areas of concern that would warrant closer monitoring by the competent authorities and a more comprehensive quality assurance in the context of supervisory or macroprudential stress testing exercise.

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 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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.627
Threshold uncertainty score0.928

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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)0.0000.000

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 head0.016
GPT teacher head0.186
Teacher spread0.170 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
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

Citations0
Published2020
Admission routes1
Has abstractyes

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