Toronto Augmented Reality Map: Enhancing citizen engagement with open government data using contemporary media platforms
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
This thesis investigates how visualization strategies and media platforms affect citizen engagement with urban public data. There is currently an international movement towards government transparency and accessible information as developed nations become more urbanized and information technology more ubiquitous. Concurrently, new media platforms (e.g., virtual and augmented reality) are evolving rapidly and show promise of mass adoption. These factors together offer design researchers a unique opportunity to develop new forms of citizen-facing media. I therefore developed an interactive augmented reality application that works with a printed map of the city of Toronto to overlay open government data as visualized digital content. An iterative practice-based research approach was used. Usability tests demonstrated that a strength of augmented reality is its facilitation of multi-user engagement. This thesis concludes by discussing how the Toronto augmented reality map can be made into an interactive citizen-facing installation in the public sphere.
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 | 0.004 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.006 | 0.001 |
| Scholarly communication | 0.002 | 0.010 |
| Open science | 0.029 | 0.011 |
| Research integrity | 0.001 | 0.002 |
| 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