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Record W2888997019 · doi:10.1111/ncmr.12135

Explaining Differences in Men and Women's Use of Unethical Tactics in Negotiations

2018· article· en· W2888997019 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.

Bibliographic record

VenueNegotiation and Conflict Management Research · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicConflict Management and Negotiation
Canadian institutionsKellogg's (Canada)
FundersFondo Nacional de Desarrollo Científico y TecnológicoComisión Nacional de Investigación Científica y Tecnológica
KeywordsEmpathyNegotiationMediationSocial psychologyPsychologyVariance (accounting)Moderated mediationDemographic economicsBusinessEconomicsPolitical science

Abstract

fetched live from OpenAlex

Abstract Emerging evidence suggests that competitiveness and empathy explain men's greater willingness to use unethical tactics in negotiations. We tested whether and how robustly they do with three distinct studies, run with three distinct populations. Simultaneous mediation analyses generally, but not completely, confirmed our expectations. In Study 1, only competitiveness mediated sex differences in unethical negotiation tactics among Chilean business students. Although empathy also explained willingness to use unethical negotiation tactics, the Chilean men and women did not differ in this regard. In Study 2, competitiveness and empathy both mediated sex differences in American business students’ intentions to lie to a client, but competitiveness explained greater variance. In Study 3, both factors explained sex differences in lying to bargaining partners for real stakes by working‐age Americans. Our findings suggest that competitiveness and empathy each explain sex differences in willingness to use unethical tactics, but the former does so more consistently.

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)0.003
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 score0.482
Threshold uncertainty score0.454

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
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 head0.197
GPT teacher head0.416
Teacher spread0.219 · 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