Increasing Citizen Engagement and Participation through eGovernment in Jordan
Bibliographic record
Abstract
Supporters of e-Government believe that this technology will be a panacea for enhancing the engagement and participation of citizens in politics and government. However, there is little empirical support for this assertion. Due to the rapid proliferation of e-Government in Jordan there is an impetus to determine how e-Government impacts citizen participation and engagement in politics and government within the country. Using qualitative phenomenological focus group interviews with 40 citizens who utilize e-Government, an effort was made to understand how this technology influences outcomes with regard to participation and engagement with government. The results indicate that those using e-Government were politically active before using the technology and have extensive experience with technology use. E-Government for the politically active serves to extend participation in the process. For individuals that lack technological savvy and/or are not politically active, e-Government alone may not be enough to increase citizen engagement and participation in politics and government.
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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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| 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 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".