Group Role Assignment with Busyness Degree and Cooperation and Conflict Factors
Why this work is in the frame
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Bibliographic record
Abstract
In collaboration, one of the most important and most challenging problems is role assignment. This paper presents a unique approach to a "group role assignment" (GRA) problem that considers two previously established constraints within the same GRA problem. They are the busyness degree of different agents, and cooperation and conflict factors between agents. The aim of solving a "Group Role Assignment with Busyness degree and Cooperation and Conflict Factors" (GRABCF) problem is to assign agents to specific tasks in order to obtain the most efficient team possible. This paper's contributions include a formalization of the GRABCF problem, a simplified matrix to express cooperation and conflict, a practical solution for this problem, and simulations to prove the benefits of solving the GRABCF problem.
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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 | 0.000 | 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