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Record W113039485

Preparing to Negotiate in a Globally Diverse Environment: An Examination of Chinese and Jewish Perspectives on Truth and Lies

2012· article· en· W113039485 on OpenAlexaff
David A. Larson, Chang Wang

Bibliographic record

VenueSSRN Electronic Journal · 2012
Typearticle
Languageen
FieldSocial Sciences
TopicConflict Management and Negotiation
Canadian institutionsThomson Reuters (Canada)
Fundersnot available
KeywordsNegotiationValue (mathematics)JudaismDeceptionIdentity (music)SociologyEthnic groupFoundation (evidence)EpistemologySocial psychologyPolitical sciencePsychologyLawAestheticsComputer scienceHistory
DOInot available

Abstract

fetched live from OpenAlex

What are a negotiator’s ethical and moral obligations during a negotiation? Should a negotiator be dedicated to achieving the greatest value possible for his or her client even though that goal may appear to require some degree of deception? Does it make a difference whether a culture has a strong religious foundation and identity? Different ethnicities and cultures obviously do not always agree as to what is right or wrong, true or false, or the degree to which one’s behavior must conform to those norms. This article will identify differing cultural perspectives towards negotiation in the course of a general discussion about negotiation but, in particular, the article will focus on how truthfulness and lying during negotiations is perceived in Chinese and Jewish culture. The following comparison between a culture that continues to develop and evolve under Communist rule and a culture that embraces long established religious values admittedly does not exhaust this complex and fascinating topic. The authors hope that readers not only find the comparison interesting and revealing, but also are inspired to further explore this cultural comparison as well as others. There always is a danger when one attempts sweeping generalizations and some of the following descriptions may be controversial. Consequently, additional dialogue is strongly encouraged. The article concludes with a “Suggestions for Instructors” section that explores additional cultural differences that can have a significant impact on both negotiations and negotiation teaching.

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)0.002
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.664
Threshold uncertainty score0.255

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.009
GPT teacher head0.264
Teacher spread0.255 · 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

Citations1
Published2012
Admission routes1
Has abstractyes

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