MétaCan
Menu
Back to cohort
Record W3166828088 · doi:10.1007/s10668-021-01390-4

Analysis on the economic effect of Sino-US trade friction from the perspective of added value

2021· article· en· W3166828088 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueEnvironment Development and Sustainability · 2021
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicGlobal trade and economics
Canadian institutionsnot available
Fundersnot available
KeywordsPerspective (graphical)Value (mathematics)EconomicsInternational economicsInternational tradeMathematicsStatisticsGeometry

Abstract

fetched live from OpenAlex

Based on the theory of trade added value, this paper discusses the potential actual trade scale and benefit damage degree of the two countries under the background of big country game by measuring the real trade scale of China and the USA, simulating the economic impact of tariffs imposed by China and the USA and utilizing Wang-Wei-Zhu (WWZ) method to decompose the potential changes in Sino-US trade. The results show that: firstly, the size of China-US trade in terms of total value is significantly overestimated and China's overall trade with the USA in 2001-2014 was overestimated by an average of 3.06 percent, of which goods trade was overestimated by 8.06 percent. Secondly, although tariff increases can reduce the degree of trade imbalance between China and the USA to some extent, the adverse effects are mutual and global, and the European Union, the Association of Southeast Asian Nations (ASEAN), Japan and Canada become the main transfer countries of Sino-US trade. Thirdly, the pattern of China's final exports and the US' intermediate exports determines that China's trade interests are more damaged than those of the USA. It is proved that there is a big gap between China and the USA in the depth and breadth of China's participation in the value chain division of labor and the trade scale measured by Gross Domestic Product is more instructive than the total value.

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.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.475

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.012
GPT teacher head0.187
Teacher spread0.174 · 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