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Record W2033343335 · doi:10.5430/rwe.v2n2p36

Breakout Financial Protection Encirclement: International Development Road of SWFs in China

2011· article· en· W2033343335 on OpenAlexvenueno aff
Xiang Jing

Bibliographic record

VenueResearch in World Economy · 2011
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicState Capitalism and Financial Governance
Canadian institutionsnot available
Fundersnot available
KeywordsSovereign wealth fundForeign-exchange reservesBusinessFinanceChinaInvestment (military)Financial systemSpecial drawing rightsOrder (exchange)Foreign direct investmentEconomicsForeign exchange riskExchange rateReserve currency

Abstract

fetched live from OpenAlex

In recent years, the foreign exchange reserves of our country rose sharply. In order to diversify foreign exchange risk and maximize the revenue of foreign exchange reserves, our country set up the first sovereign wealth funds (SWFs) in 2007, namely China Investment Corporation (CIC). The main source of funds was 200 billion dollars in foreign exchange reserves bought by Ministry of Finance from issuing 1.55 trillion yuan special treasury bonds. As a new SWF, CIC lacked proper investment management mechanisms and also faced high domestic expected investment return and a variety of investment impediments on international financial markets. Therefore, this paper will interpret how to breakout the shackles and cope with the uncertainty of the development process, and analyze the development and expansion road of SWFs in China.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.051
Threshold uncertainty score0.101

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0020.001
Scholarly communication0.0020.002
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.073
GPT teacher head0.276
Teacher spread0.204 · 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

Citations0
Published2011
Admission routes1
Has abstractyes

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