Power asymmetry in conflict resolution with application to a water pollution dispute in <scp>C</scp>hina
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
Abstract The concept of power asymmetry is incorporated into the framework of the Graph Model for Conflict Resolution (GMCR) and then applied to a water pollution dispute in China in order to show how it can provide strategic insights into courses of action. In a new definition of power asymmetry, one of the decision makers (DMs) in a conflict can influence the preferences of other DMs by taking advantage of additional options reflecting the particular DM's more powerful position. The more powerful DM may have three different kinds of power: direct positive, direct negative, or indirect. It is useful to analyze a model of a conflict without power asymmetry, and then to analyze a power‐asymmetric model. As demonstrated by analysis of the water quality controversy that took place at the border separating the Chinese provinces of Jiangsu and Zhejiang, this novel conflict resolution methodology can be readily applied to real‐world strategic conflicts to gain an enhanced understanding of the effects of asymmetric power.
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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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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