Visualization tools, argumentation schemes and expert opinion evidence in law
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
New models of evidential reasoning have been closely tied in with the development of visualization tools in artificial intelligence, especially automated systems for argument diagramming. Surveying several models and visualization tools recently developed in artificial intelligence, this paper argues that any discussion of visualization methods or tools of this sort should focus on their suitability for visualizing argumentation schemes, including critical questions. The classic scheme, used in this paper to illustrate how schemes need to be a vital part of advancing argumentation technology in tools for evidence visualization in law, is that for argument from expert opinion. The visualization of argumentation schemes is illustrated using a new version of the scheme, which takes into consideration Supreme Court rulings on the admissibility of expert witness testimony.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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