An argumentation map prototype to support decision-making in spatial planning
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
Collaborative decision-making usually entails argumentation - the exchange of personal views on certain topics, in particular using logical reasoning. Argumentation is often structured into discussions with contributions by individual participants responding to each other. In spatial decision situations, most discussion contributions will contain geographic references. Argumentation Maps were developed to support geographically referenced discussions by cartographic visualization and query functionality. This concept makes geographic references in discussion contributions explicit and uses them for linking text messages to maps, and vice-versa. Based on an analysis of previous work on discussion and decision support in spatial planning, we propose a set of requirements and design guidelines for implementing Argumentation Maps. These guidelines are centred on two main issues: user friendliness and support of open standards. A prototype which implements interoperability specifications of the Open Geospatial Consortium demonstrates the usefulness and usability of Argumentation Maps for public participation in spatial planning.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 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