Collaborative Problem Solving Through Creativity in Problem Definition: Expanding the Pie
Bibliographic record
Abstract
The classic models of two party problem solving in situations of potential conflict are reviewed and the growing impetus for a process that would encourage collaborative win‐win solutions is summarized. In is demonstrated that in‐win collaboration requires innovative thinking, and that a four stage process of deliberate creativity with a track record of success is described. The process, called Simplex, emphasizes ‘out of the box’ thinking in problem defining (before solving) as the key to making a perceived ‘fixed pie’ larger, moving beyond the shackles of zero‐sum, win‐lose, compromise thinking. If a problem can be conceptualized from a new angle in such a way that each party believes its resolution would provide a high level of satisfaction, then the parties will be more likely to work together collaboratively. This process uses four specific creative thinking skills. A case study is described in which the Simplex process was used in union management bargaining. In the case study, when the creative process was deliberately applied, success was achieved in building trust and developing expanded pies and new solutions. However, when the process was abandoned, the trust was lost, no creative solutions were developed, and a sub‐optimal lose‐lose situation resulted. A two‐dimensional diagnostic model which shows the relationship between skill level in the process and motivation to use it is provided. This model defines four modes of pure and mixed distributive and integrative bargaining.
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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 | 0.008 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.002 | 0.013 |
| Scholarly communication | 0.011 | 0.009 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".