An Impact of Negotiation Profiles on the Accuracy of Negotiation Offer Scoring System? Experimental Study
Bibliographic record
Abstract
In this paper an impact of the party's negotiation profile on the misperception of the preferential information provided to the negotiating parties is studied.In particular, the problems with determining an adequate and preferentially correct negotiation offer scoring system is analyzed, when the parties are supported in their decision analyses by means of the SAW technique.In the analyses we use the negotiation data from bilateral negotiation experiments conducted by means of the Inspire negotiation support system.To determine the negotiators' profiles the Thomas-Kilmann Conflict Mode Instrument was used, which allows to describe their general negotiation approach using two dimensions of assertiveness and cooperativeness.The accuracy of scoring systems was defined as the extent to which the negotiator's individual scoring system (agent's system) is concordant to the preferential information provided by the negotiator's superior (principal's system) in the form of verbal and graphical descriptions, and measured by means of ordinal and cardinal accuracy indexes.
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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 | 0.026 | 0.210 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".