Negotiating power: Agenda ordering and the willingness to negotiate in asymmetric intergroup conflicts.
Bibliographic record
Abstract
In this research, we investigated how group power influences the way members of groups in asymmetrical conflict approach intergroup negotiations. Drawing on theories of negotiations and of intergroup power, we predicted that group power would interact with features of the proposed negotiating agenda to influence willingness to come to the table. Based on the negotiation literature, we focused on 2 types of sequential negotiation agendas: 1 beginning with the discussion of consequential issues before less consequential issues (consequential first) and 1 leaving the discussion of consequential issues until after less consequential issues are discussed (consequential later). Because they are motivated to advance changes to their disadvantaged status quo, we expected low-power group members to favor consequential first over consequential later invitations to negotiate. High-power group members, motivated to protect their advantage, were expected to show the reverse preference. Converging evidence from 5 experiments involving real-world and experimental groups supported these predictions. Across studies, participants received an invitation to negotiate from the other group involving either a consequential first or consequential later agenda. Low-power group members preferred consequential first invitations because these implied less stalling of change to the status quo, and high-power group members preferred consequential later invitations because these invitations seemed to pose less threat to their position. Theoretical and practical implications for negotiations research and conflict resolution are discussed.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.009 | 0.043 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".