Multidimensional Web GIS Approach for Citizen Participation on Urban Evolution
Bibliographic record
Abstract
Web-mapping has been widely used to facilitate citizen participation in smart cities. Web-mapping has evolved from 2D static maps towards more dynamic and immersive 3D worlds such as virtual globes and scenes. Although current technologies allow us to build multidimensional representations, there is still a lack of research studies on how to further leverage them to foster citizen participation. Information on space–time changes can be an important asset for a successful citizen participation process. Citizens may need to track the evolution of their city over space and time, and how their participation will impact the urban planning and decision-making process. Consequently, the main objective of this research study is to design and develop a multidimensional (2D, 3D, 4D) web-mapping platform where citizens can better assess and understand the spatiotemporal evolution of their cities. User testing was conducted to assess the multidimensional representation of the animations used, and the spatiotemporal mechanism and interface features. Results showed that it is recommended to integrate spatiotemporal simulations to citizen participation platforms so citizens can better assess the impacts of their choices. We also assessed that 3D does not always communicate information better than 2D. Future work will aim at testing the platform in a consultation process with a representative sample of participants.
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How this classification was reachedexpand
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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.004 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".