Public Engagement with Internet Voting in Edmonton: Design, Outcomes, and Challenges to Deliberative Models
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
In September 2012, the City of Edmonton launched a four-month strategy to engage a range of citizens in the development of a policy proposal for the use of Internet voting in civic elections. A variety of initiatives were implemented, including public opinions surveys, roundtable advisory meetings with seniors and other stakeholder, and a mock “Jellybean” online election to test the technology. At the core of the public involvement campaign was a Citizens’ Jury – a deliberative forum which engaged a group of citizens, demographically and attitudinally representative of the city’s population, in assessment of Internet voting and the development of recommendations to city council. While the Jury reached a verdict supportive of Internet voting, policymakers in Edmonton rejected the policy proposal. In light of the Edmonton experience, we highlight factors that contribute to the ineffectiveness of deliberative experiments and discuss some challenges for public participation at the local level.
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 | 0.002 | 0.002 |
| 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 | 0.001 |
| 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