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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 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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.097
Threshold uncertainty score0.324

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0020.000
Scholarly communication0.0020.001
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0970.032

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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
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
Published2003
Admission routes1
Has abstractyes

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