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Record W3102506481 · doi:10.5430/jms.v11n4p1

Under the Epidemic Situation: The Study of Bilateral Trade Zone and Agreement Between China and Korea

2020· article· en· W3102506481 on OpenAlexvenueno aff
Naipeng Bu, Haiyan Kong, Mumtaz Hussain, Sareema Fatima

Bibliographic record

VenueJournal of Management and Strategy · 2020
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicEconomic Zones and Regional Development
Canadian institutionsnot available
Fundersnot available
KeywordsChinaTourismTariffBusinessGovernment (linguistics)International tradeFree trade zoneForeign direct investmentCoronavirus disease 2019 (COVID-19)World tradeEconomic growthEconomicsGeography

Abstract

fetched live from OpenAlex

In 2019, Coronavirus outbroke, and many countries in the world were impacted by COVID-19. The COVID-19 epidemic has clouded the global economic outlook. In the current dynamic situation of the world, businesses have need to integrated internationally. Chinese and Korean government has progressively upgraded the free trade zones (FTZ) to attract greater foreign investment and tourism development. In this article, we discuss the important factors for tariff concessions in the China and Korea free trade agreement (FTA). Further, according to Korean Tourism Development Bureau (KTDB), in perspective of tourism China and Korea are more prominent in the Universal Economy. Chinese and Korean tourists are rapidly integrated in the world. Consequences created by Free Trade Zone, it is suggested that both countries should consider strategies to combat negative factors by diversifying the range of products and services and both countries can also use tourism-related professionals in areas that support FTZ's economic development.

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)0.001
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 score0.279
Threshold uncertainty score0.214

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 head0.067
GPT teacher head0.231
Teacher spread0.165 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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
Published2020
Admission routes1
Has abstractyes

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