Conflict Resolution in Construction Disputes Using the Graph Model
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.
Bibliographic record
Abstract
A formal approach is presented for systematically resolving construction conflicts. Using an actual case study, a decision support system based on the graph model for conflict resolution (GMCR II), is employed to effectively investigate the strategic interactions that took place between an owner and a general contractor concerning the financing of a construction project. The conflict analysis process considers the decision participants, their decision options, and their relative preferences when modeling the dispute. GMCR II is then used to perform an in-depth stability analysis in order to ascertain the possible compromise resolutions or equilibria. In the case study, GMCR II correctly predicts the sequence of decisions that took place in the dispute and furnishes an array of useful strategic insights about the conflict. Moreover, a sensitivity analysis is executed to determine how changes in preferences can affect the equilibrium results. This conflict resolution procedure is useful for both researchers and practitioners to better deal with the dispute-prone nature of the construction industry.
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 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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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