Evaluating the Effectiveness of Three Dimensional Geovisualization Tools in Communicating Climate Change Impacts, A PEI Case Study
Bibliographic record
Abstract
Three-dimensional geographic visualization (3D geovisualization) tools have been praised as a solution to the challenge of communicating climate change impacts by capturing public interest, making the issues more personal, and motivating users to take action. However, evaluation methods are not standardized, especially with novice and expert users. Using a combination of workshop surveying and usability testing, I addressed this issue by studying the Coastal Impact Visualization Environment (CLIVE) tool, which allows users to visualize potential sea-level rise and coastal erosion scenarios on PEI (Prince Edward Island). I found that geovisualization tools have the capability to educate and engage users about potential climate change impacts, but generally fade from the users’ memories over time, leading to a lack of overall motivation to take climate change action. This has paved the way for the development of a pilot cybercartographic atlas to keep the discussion about climate change impacts accessible.
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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 | 0.011 | 0.032 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".