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Record W3204578322

Growth locomotive China

2003· preprint· en· W3204578322 on OpenAlexaboutno aff
Waltraut Urban

Bibliographic record

VenueRePEc: Research Papers in Economics · 2003
Typepreprint
Languageen
FieldEconomics, Econometrics and Finance
TopicEconomic Zones and Regional Development
Canadian institutionsnot available
Fundersnot available
KeywordsQuarter (Canadian coin)ChinaPosition (finance)EconomicsPopulation growthPopulationBalance of tradeWorld economyDevelopment economicsGeographyInternational tradeDemographyPolitical scienceFinance
DOInot available

Abstract

fetched live from OpenAlex

Overall economic growth in China is expected to reach 8.5% in 2003, the highest rate since the Asian economic crisis in 1997/98. However, the expansion was harshly interrupted in the second quarter of the year by the outbreak of SARS (severe acute respiratory syndrome) economic activity in certain sectors and regions was paralysed as a consequence of panic reactions on the one hand and far-reaching preventive measures, including travel-bans, quarantine, etc. on the other. The GDP growth rate declined to just 6.7% in the second quarter, after 9.9% growth in the first quarter of 2003. But growth resumed quickly when the disease was brought under control, reaching 9.1% in the third quarter. This gives an average 8.5% growth rate for the first nine months, which is expected to continue throughout the rest of the year and probably in 2004 as well. Such a scenario would be based on the assumption that the stimulating effects of a faster growing world economy in the year to come and policy measures to prevent an over-heating of the Chinese economy will roughly balance each other. As a consequence of its large population and rapid economic growth over the past 25 years, China has become the sixth largest economy in the world and the second largest in the region. Due to its export-oriented growth strategy, China¿s position is even more prominent in trade, ranking fourth in the world already. Moreover, China is particularly important in certain categories of exports (e.g. textiles & clothing, shoes, electric appliances, TV sets, cameras ) but imports as well (e.g. basic metals including steel, soybeans). It is in these product groups that China may significantly affect world prices and/or may impact on the development of industry in certain countries.

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)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.691
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0010.001

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 head0.042
GPT teacher head0.270
Teacher spread0.228 · 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 designTheoretical or conceptual
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
Published2003
Admission routes1
Has abstractyes

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