Bibliographic record
Abstract
This article examines the impact of information and communications technologies (ICTs) on electronic democracy at the local government level. It concentrates on measures taken by local governments in the United States, Canada, and the United Kingdom to transform their relationship to citizens by means of e-democracy. The emphasis on democracy is particularly important in an era when governments at all levels are said to be facing a democratic deficit (Hale, Musso, & Weare, 1999; Juillet & Paquet, 2001). Yet, as this article argues by means of an examination of the available evidence in the United States, Canada, and the United Kingdom, e-democracy has failed to deepen democracy at the local level, this at a time when local government is said to be becoming more important in people’s lives (Mälkiä & Savolainen, 2004). The first part of the article briefly summarizes the arguments on behalf of the growing importance of the city as a major locus of economic and political activity. It then discusses how e-democracy relates to e-government in general. Next, it discusses the normative relationship between two models of democracy and ICTs. The article then reviews the evidence to date of e-democracy at the local level of government in the aforementioned countries. Finally, it discusses why e-democracy has not lived up to expectations highlighting the dominance of neo-liberalism.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.010 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".