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Record W6980569159

China Economic Update, May 2018 : Investing in High-Quality Growth

2018· report· en· W6980569159 on OpenAlexaboutno aff

Bibliographic record

VenueThe World Bank Open Knowledge Repository (World Bank) · 2018
Typereport
Languageen
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsChinaConsumption (sociology)Quarter (Canadian coin)Real gross domestic productProduction (economics)Economic indicatorEconomic expansionEconomic forecastingGross domestic productEconomic sector
DOInot available

Abstract

fetched live from OpenAlex

The World Bank Economic Update provides
\n an overview of recent economic and social developments and
\n policies in China. Economic activity in China remains
\n resilient, with GDP growing by 6.9 percent in 2017 and 6.8
\n percent year on year (yoy) in the first quarter of 2018.
\n Consumption continues to drive growth, while net exports,
\n which led the growth acceleration in 2017, were not a source
\n of growth in Q1 2018. From the production perspective, “new
\n economy” sectors are becoming a more prominent source of
\n growth. Despite their small GDP share, software and IT
\n services are rising at double-digit rates and contributed
\n 1.1 percentage points to growth in Q1 2018.

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)0.022
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Scholarly communication, Open science, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow), Open science, Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.392
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0220.001
Meta-epidemiology (narrow)0.0040.003
Meta-epidemiology (broad)0.0060.001
Bibliometrics0.0040.005
Science and technology studies0.0020.003
Scholarly communication0.0030.002
Open science0.0120.009
Research integrity0.0010.005
Insufficient payload (model declined to judge)0.0030.026

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 head0.056
GPT teacher head0.352
Teacher spread0.296 · 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; both teacher heads agree on what is shown here.

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
Published2018
Admission routes1
Has abstractyes

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