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Record W2376410634

A Comparative Study of Financial Supervision between China and Canada

2013· article· en· W2376410634 on OpenAlexaboutno aff
Zuo Lian-cu

Bibliographic record

VenueChanjing pinglun · 2013
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicInsurance and Financial Risk Management
Canadian institutionsnot available
Fundersnot available
KeywordsFinancial regulationLegislationAccountingChinaBusinessFunction (biology)Agency (philosophy)Financial riskDirectiveFinanceEconomicsLawPolitical science
DOInot available

Abstract

fetched live from OpenAlex

Canada is recognized a relatively stable country on financial industry in the world,the reason is that Canada have traditional stable manage style and effective Financial Supervision system.It will have positive significance for perfecting China's financial supervision to study Canada's financial regulatory system and its features.This article analyses historical development process,of Canadian financial supervision system,discusses the main contents which includes: Supervision system present Two levels and several directions,and takes the risk as the core of Supervisor of Framework,and summarizes the basic Characteristics which includes: financial practice catalytic,take independence and coordinate as one,risk resistance,function regulation and elasticity regulation,regulation according to law,and particular manage ideas etc.At the same time,some enlightenments are risen to China,which includes: regulatory model by sub-sector regulatory agency to mix function regulatory,establish scientific and reasonable risk assessment mechanisms and practices,improve coordination among financial regulators,strengthen finacial legislation,improve the finacial regulatory laws,supervision according to law.

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)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.046
Threshold uncertainty score0.331

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.006
Science and technology studies0.0040.001
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.034
GPT teacher head0.221
Teacher spread0.186 · 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 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
Published2013
Admission routes1
Has abstractyes

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