A Proposed Practical Problem-Solving Framework for Multi-Stakeholder Initiatives in Socio-Ecological Systems Based on a Model of the Human Cognitive Problem-Solving Process
Bibliographic record
Abstract
A practical problem-solving framework is proposed for multi-stakeholder initiative (MSI) problem-solving processes involving socio-ecological systems (SES), so-called wicked problems, based on insights borrowed from a model of the individual human, cognitive problem-solving process. The disciplined facilitation of the multi-stakeholder process, adhering to the steps recognized in the individual process, is meant to reduce confusion and conflict. Obtaining a one- to three-sentence human-language description of the desired system state, as a first step, is proposed in multi-stakeholder initiatives for reasons of goal congruence and trust building. The systematic, stakeholder-driven subdivision of obstacles into larger numbers of simpler obstacles is proposed in order to obtain a list of "what needs to be done," inviting a more rational and goal-driven conversation with resource providers. Finally, obtaining and maintaining stakeholder buy-in over the course of the problem-solving effort is reinforced by reflecting back to all stakeholders, as a communication device, a dynamic, visual problem-solving model, taking into account the diversity of cognitive and individual capacities within the stakeholder group in its presentation. Mathematical parameters for gauging applicability of the proposed framework are discussed.
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How this classification was reachedexpand
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 | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".