Towards a spatial imperative in public urban development geovisual analysis and communication
Bibliographic record
Abstract
Despite advances in GIScience and geovisualization, public consultation for urban development often lack analytical depth or visualization methods that deliver transparent communication and democratic access. Typical methods for engaging the public include the use of architectural designs, artists’ renderings, engineering drawings, and physical models (Gill, Lange, Morgan, & Romano, 2013). These methods of urban development communication do little to accommodate portions of the population that are not design-oriented (Al-Kodmany, 1999). This thesis seeks to bridge the gap between GIScience, geovisualization, and urban development through the development of an evaluation framework for existing urban development visualizations. Next, it evaluates visualizations produced for a new development in the District of North Vancouver named “The Residences at Lynn Valley.” Following this evaluation, it proposes a set of visibility analyses that aim to reveal the intangible visual impact of future developments. This research provides the basis for future evaluative and analytical work in GIS and geovisualization for urban development.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.013 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.006 | 0.024 |
| Scholarly communication | 0.019 | 0.009 |
| Open science | 0.001 | 0.009 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".