Electronic democracy's deliberative potential: dissecting the Canadian polity and the challenges ahead
Bibliographic record
Abstract
The purpose of this paper is to examine the still nascent emergence of e–democracy in Canada and its potential to foster constructive online deliberation both now and into the future. There can be little question that with the advent of the internet and a host of participatory tools denoted as Web 2.0, democratic processes are beginning to gravitate online. In attempting to understand the deliberative potential of this online realm, it is important to examine the individualised incentives and ethics of citizens, as well as how information flows stemming from traditional media and new forms of social media impact awareness and action (or inaction). Moreover, we consider the difficult alignment between e–democracy as a national project and the multi–layered realities of a federated polity, a variable often over–looked in e–democracy discussions but one adding significant complexity. Based upon an assessment of the Canadian experience to date, proposed directions for strengthening democratic deliberation in an online era are put forth and discussed.
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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 | 0.008 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.005 | 0.008 |
| Science and technology studies | 0.030 | 0.021 |
| Scholarly communication | 0.017 | 0.005 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.008 | 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".