Bibliographic record
Abstract
정부정보는 한 국가의 국민으로 살아가기 위해서는 누구에게나 필요하다. 인터넷 보급으로 필요한 정부 정보에 보다 쉽게 접근하여 이를 이용할 수 있으며, 특히 전자정부 웹사이트를 통해 필요한 정부정보를 얻을 수 있는 길이 열리고 있다. 본 연구에서는 전자정부 프로젝트를 가장 잘 추진하고 있는 미국, 캐나다, 오스트레일리아의 전자정부에 대하여 조사해 보고, 한국의 전자정부에 대하여 조사하여 전자정부 웹사이트를 통해 보다 유용한 정부 정보를 찾을 수 있는 방법을 모색하여 보았다. Accurate and current government information is essential to any member of that country. Now it has become possible to access government information with greater ease and convenience on the internet. This study examines e-government websites of the U. S. Canada Australia, the leading countries in the e-government project, and provides ways to improve the e-governments website of Korea.
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.
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 | 0.004 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.018 |
| Open science | 0.001 | 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".