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Record W2040526393 · doi:10.1177/0003603x15573756

The Economic Link between China and North America

2015· article· en· W2040526393 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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueThe Antitrust Bulletin · 2015
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicGlobal Financial Crisis and Policies
Canadian institutionsMcGill University
Fundersnot available
KeywordsChinaFinancial crisisFinancial marketProsperityEconomicsPositive correlationNegative correlationInternational economicsInternational tradeGeographyFinanceMacroeconomicsEconomic growth

Abstract

fetched live from OpenAlex

China’s prosperity may upset others. Will a rising China reduce the growth rate of other countries? We address the question with statistics by comparing the securities market indices of China with those of the United States and Canada. We ask whether the financial markets—East and West—are positively correlated or negatively correlated. We find a moderate positive correlation. This correlation decreases during extreme market circumstances, particularly during market crashes. The correlation becomes closer—we think better for cooperation—during times of improved international cooperation. The correlation diminishes—we think worse for cooperation—when abrupt negative contingencies arise in the global market. The data show that the correlation increased after China joined the World Trade Organization and dramatically decreased after the financial crisis in 2008. Moreover, our lead and lag analysis shows that North America’s markets forecast later developments in China’s market. In general, there is a trend in the positive correlation between the two economies.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.489
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0000.004

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 head0.027
GPT teacher head0.217
Teacher spread0.190 · 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