More Art Than Science: The Sources and Effects of Stylistic Variation in Visualization for Planning and Design
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
Visioning exercises using computer-based environmental visualization hold significant promise for communicating information and engaging communities in the development and review of planning proposals. The field of visualization research and practice has achieved significant advances in computer technology to the point where it is now possible to represent alternative planning and engineering scenarios with a high degree of photographic realism, data-driven accuracy, and spatial and temporal interactivity. Despite the noteworthy benefits and developments in the field of environmental visualization technology comparatively little research has investigated how visualizations are used in urban planning practice. In particular, research is needed that examines how visualization presentation is affected by the social context of planning practice and the independent judgment of the preparer, which may in turn influence plan evaluation and decision making. In this paper I discuss the significance of visualization for urban planning and design and present the results from a study where students and representatives of a citizen-led planning committee evaluated four visualization presentation styles according to perceived realism, credibility and preference for the visualized environmental plans.
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 | 0.001 | 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) | 0.000 | 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