Managing Conflict Resolution and Perceptions: An Approach Leveraging the Thomas‐Kilmann Conflict Mode Theory
Bibliographic record
Abstract
ABSTRACT Conflict resolution management is a process whereby two or more parties engage toward an agreeable solution to a dispute. In this study, we propose a methodology to start a structured process of resolving complex conflicts between parties that previously avoided any form of engagement. We leverage the Thomas‐Kilmann conflict mode theory to guide our methodological design that we have termed SACRE (Symmetric Asynchronous Conflict Resolution Environment). SACRE was designed for and implemented in a real‐world project related to the complex topic of the Israeli–Syrian conflict. We then tested the effectiveness of SACRE in an academic setting and examined through statistical analysis its impact on the understanding and the perceptions of the conflict. Our findings indicate that SACRE, which offers an approach to communication among parties in conflict, can enhance knowledge of the issues of contention and bridge the conflict's perceptual gap.
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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 | 0.019 | 0.031 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.007 | 0.003 |
| Science and technology studies | 0.003 | 0.010 |
| Scholarly communication | 0.007 | 0.009 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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 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".