Ulysse: a qualitative tool for eliciting mental models of complex systems
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 Stakeholders involved in the definition of managerial problems perceive and internalize the complexity of these problems as mental models. These models are not always made explicit, which can lead to misunderstandings and conflicts. This article presents Ulysse, a tool that enables stakeholders to progressively elicit their mental models as causal loop models. Ulysse uses web technologies that store information in a database and interactively display the modeling results. It is based on matrix calculation that facilitates statistical operations and provides better understanding of the model structure. Analysis and comparison of individual models reveal the most important variables and relationships among them as a basis for identifying key issues, divergent and convergent opinions between stakeholders. Ulysse has been tested in the context of regional economic development in Atlantic Canada. The tool was designed to support managers, during interviews, in building qualitative models of indicators. Copyright © 2010 John Wiley & Sons, Ltd.
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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 | 0.023 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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