E-Government Readiness Assessment for Government Organizations in Developing Countries
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
ICT has become an increasingly important factor in the development process of nations. Major barriers can be met in the adoption and diffusion of e-government services depending on the readiness of a country in terms of ICT infrastructure and deployment. This study aims to define organizational requirements that will be necessary for the adoption of e-government to resolve the delay of ICT readiness in public sector organizations in developing countries. Thus, this study contributes an integrated e-government framework for assessing the ICT readiness of government agencies. Unlike the existing e-government literature that focuses predominantly on technical issues and relies on generic e-readiness tools, this study contributes a comprehensive understanding of the main factors in the assessment of e-government organizational ICT readiness. The proposed e-government framework comprises seven dimensions of ICT readiness assessment for government organizations including e-government organizational ICT strategy, user access, e-government program, ICT architecture, business process and information systems, ICT infrastructure, and human resource. This study is critical to management in assessing organizational ICT readiness to improve the effectiveness of e-government initiatives.
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 | 0.001 | 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 | 0.000 |
| Scholarly communication | 0.000 | 0.005 |
| 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