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Record W2009698689 · doi:10.1177/0021886303260547

Negotiating with the Chinese

2003· article· en· W2009698689 on OpenAlexaff
Michael V. Miles

Bibliographic record

VenueThe Journal of Applied Behavioral Science · 2003
Typearticle
Languageen
FieldSocial Sciences
TopicConflict Management and Negotiation
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsNegotiationContext (archaeology)ChinaPerspective (graphical)Face (sociological concept)Action (physics)Public relationsClosing (real estate)Chinese cultureSociologyPsychologySocial psychologyPolitical scienceComputer scienceLawSocial science

Abstract

fetched live from OpenAlex

Negotiation is a context sport. It demands attention to multiple motivations, agendas, and preferences. Negotiation across culture complicates context by highlighting the cultural realities of the negotiation dance. Without awareness of appropriate cues to follow and sensitivity to the possibilities for action opening and closing throughout the negotiation process itself, foreigners face little possibility of successful conclusion to negotiation in a cross-cultural setting. This article makes explicit seven principles driving the act of negotiation in a Chinese context. Within the framework of an actual negotiation for delivery of training for Chinese managers, the author describes what these principles look like as they were enacted through Chinese negotiating practices and how he responded to them from both a theoretical and a practical perspective. In the face of Chinese negotiation principles, the article suggests a range of practical strategies for successful—and respectful—negotiation in China.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.006
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.025
Threshold uncertainty score0.049

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0100.010
Scholarly communication0.0060.004
Open science0.0010.006
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0060.001

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 head0.021
GPT teacher head0.321
Teacher spread0.300 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
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

Citations46
Published2003
Admission routes1
Has abstractyes

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