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Macro and financial-sector policies to sustain the recovery

2010· book-chapter· en· W4233387629 on OpenAlexaboutno aff

Bibliographic record

VenueOECD economic surveys. Canada · 2010
Typebook-chapter
Languageen
FieldBusiness, Management and Accounting
TopicState Capitalism and Financial Governance
Canadian institutionsnot available
Fundersnot available
KeywordsMoral hazardShareholderFinancial systemFinancial crisisBusinessFinancial marketCapital marketBalance sheetFinanceFinancial regulationEconomicsMonetary economicsCorporate governanceMarket economyIncentiveMacroeconomics

Abstract

fetched live from OpenAlex

Canada benefited from many strengths such as a less-leveraged financial sector, few subprime mortgages and sound corporate balance sheets as it weathered the global economic crisis of 2007-09. Actions by the monetary and fiscal authorities have stabilised financial markets and provided substantial support to the economy. With upturns in global trade and in commodity prices, the recovery is now well under way, but the pace of expansion is projected to slow later in 2010 and in 2011 as policy stimulus is withdrawn, inventory rebuilding runs its course and households reduce their spending growth in reaction to high indebtedness. In the longer term, Canada faces the same reform challenges that other OECD countries face to allow credible exit paths for big banks and to increase competition, contestability and shareholder oversight in this sector. International efforts to strengthen financial-system resilience should take inspiration from Canada’s own model of risk-based prudential regulation, which successfully held banking risks in check. Reforms that imply large increases in bank capital should be accompanied by greater market discipline to contain moral hazard and spur efficiency. Securities markets should be better regulated in order to attract foreign capital, encourage competitive impulses and improve macro-prudential regulation.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.404
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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)0.0020.000

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 head0.009
GPT teacher head0.169
Teacher spread0.160 · 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.

Study designNot applicable
Domainnot available
GenreOther

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
Published2010
Admission routes1
Has abstractyes

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