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Record W4247624189 · doi:10.1108/oxan-db210595

China rebalancing continues, but debt risks rise

2016· other· en· W4247624189 on OpenAlexaboutno aff

Bibliographic record

VenueEmerald expert briefings · 2016
Typeother
Languageen
FieldEconomics, Econometrics and Finance
TopicGlobal Financial Crisis and Policies
Canadian institutionsnot available
Fundersnot available
KeywordsRenminbiChinaVolatility (finance)DebtBondQuarter (Canadian coin)Interest rateEconomicsInvestment (military)BusinessExchange rateMonetary economicsInternational economicsFinancial systemEconomic policyFinanceGeographyPolitical science

Abstract

fetched live from OpenAlex

Subject The macroeconomic outlook for China. Significance GDP grew by 6.7% year-on-year in the first quarter of 2016 to almost 15.9 trillion renminbi (2.4 trillion dollars), the National Bureau of Statistics (NBS) reported on April 15. Over-reliance on investment and policy stimuli are carrying the economy, with only a slow structural rebalancing towards demand needed for long-term sustainable growth. Mounting debt is of immediate concern for the corporate and financial sectors, and for the outlook this year, the first in the 13th Five-Year Plan period. Impacts Markets will be especially sensitive to data releases and policy signals, making for more volatility. The possibility of a US rate hike complicates China's efforts to hold its interest rates down while controlling outflows. Conversion of debt into bonds and some relaxation of social security contribution requirements should take some pressure off localities.

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: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.044
Threshold uncertainty score0.148

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0010.001
Scholarly communication0.0030.002
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0440.007

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 head0.024
GPT teacher head0.259
Teacher spread0.235 · 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
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
Published2016
Admission routes1
Has abstractyes

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