Bibliographic record
Abstract
As e-government becomes increasingly pervasive in modern public administrative management, its influence on organizations and individuals has become hard to ignore. It is therefore timely and relevant to examine e-governance—the fundamental mission of e-government. By adopting a stakeholder perspective and coming from the strategic orientation of control and collaboration management philosophy, this study approaches the topic of e-governance in e-government from the three critical aspects of stakeholder management: (1) identification of stakeholders, (2) recognition of differing interests among stakeholders, and (3) how an organization caters to and furthers these interests. Findings from the case study allow us to identify four important groups of stakeholders known as the Engineers, Dissidents, Seasoners, and Skeptics who possess vastly different characteristics and varying levels of acceptance of and commitment towards the e-filing paradigm. Accordingly, four corresponding management strategies with varying degrees of collaboration and control mechanisms are devised in the bid to align these stakeholder interests such that their participation in e-government can be leveraged by public organizations to achieve competitive advantage.
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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 | 0.005 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.067 | 0.014 |
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".