Computerized DSS for Construction Conflict Resolution under Uncertainty
Why this work is in the frame
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Bibliographic record
Abstract
Due to the inherent nature of construction projects, conflicts are unavoidable among the various parties involved. Such conflicts often delay projects and cause losses for all parties. This paper presents the development of a decision support system (DSS) to help in resolving construction disputes. The DSS integrates the elimination method to shortlist promising resolutions to a conflict, the graph model for conflict resolution to determine the best resolution that satisfies all decision makers’ preferences, and the information gap theory to consider uncertain decision preferences. A prototype system has been developed and a case study of a construction conflict used to demonstrate its features. The presented methodology for construction conflict resolution is useful for both researchers and practitioners to better deal with the dispute-prone nature of the construction industry under uncertainty and lack of information. In this paper, the proposed prototype successfully simulated and predicted the sequence of decisions that took place in the case study dispute, in the presence of uncertainty.
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it