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Record W4404366632 · doi:10.5539/ijel.v14n6p180

Cultural Factors Influencing Interest Contention of China’s Business Dispute Settlement: A Discourse Information Perspective

2024· article· en· W4404366632 on OpenAlexvenueno aff
Tingting Guo, Dong Wang, Qiusheng Zheng, Jingyi Cao, Fangyuan Liu

Bibliographic record

VenueInternational Journal of English Linguistics · 2024
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicDispute Resolution and Class Actions
Canadian institutionsnot available
Fundersnot available
KeywordsPerspective (graphical)ChinaSettlement (finance)BusinessLaw and economicsPublic relationsPolitical scienceSociologyLawFinanceComputer science

Abstract

fetched live from OpenAlex

Interest contention is the embodiment of the essential issue in the process of business dispute resolution. In order to realize the interest competition in the settlement of business disputes, the litigants with different interest positioning and interest demands can use many information resources to express, cling to and fight for their interests under the influence of various factors. The present study attempts to make a discourse analysis of the cultural factors that influence the conflict of interests in China’s business dispute court hearings from the perspective of Discourse Information Theory. This research adopts the discourse information analysis method with the aid of “Legal Information Processing System Corpus (CLIPS)”. The analysis is mainly carried out from the perspective of cultural value, thinking mode, business culture and legal culture embodied in the interest competition in the settlement of business disputes. Under the influence of cultural factors, discourse information has different characteristics in the interests of business dispute resolution. The cultural factors and discourse information characteristics that influence interest competition in China’s business dispute settlement found in this study will complement and enrich the cultural research on interest competition in business dispute resolution, and promote the integration of different disciplines of business, law and linguistics, which has certain theoretical and practical significance.

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)0.000
metaresearch head score (Gemma)0.013
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.964
Threshold uncertainty score0.995

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.013
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.002
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 head0.020
GPT teacher head0.293
Teacher spread0.274 · 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.

Study designTheoretical or conceptual
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
Published2024
Admission routes1
Has abstractyes

Explore more

Same venueInternational Journal of English LinguisticsSame topicDispute Resolution and Class ActionsFrench-language works237,207