Analyzing the Usability of an Argumentation Map as a Participatory Spatial Decision Support Tool
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
Argumentation Maps support participants in geographically referenced debates as they occur, for example, as part of urban planning processes. In a quasi-naturalistic case study, 11 student participants discussed planning issues on the University of Toronto downtown campus. The analysis of this case study focuses on general usability aspects of an Argumentation Map prototype, such as cost of entry, efficiency, interactivity, and connectivity. By applying usability analysis methods from the field of human-computer interaction, we evaluate the learnability, memorability, and user satisfaction with this tool’s functionality. Our findings indicate that the participants were generally satisfied, but we include specific suggestions for improving the functionality of Argumentation Maps, e.g., with respect to map navigation, display of discussion contributions, and online status of participants. On a more general level, this case study contributes to the methods spectrum of research into participatory spatial decision support systems as an example of user testing in a realistic decision-making context.
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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 | 0.002 | 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) | 0.001 | 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