A Generic Modeling Approach for E-Administration Based on Holonic Systems - Case Study of Collective Move Due to a Natural Disaster
Bibliographic record
Abstract
E-administration is one of the areas that continues to attract the interest of both researchers and governors. It is one of the best areas of application of Information and communication technology (ICT). The objective of e-administration is not new; it is that of constantly improving the quality of service provided to citizens through the use of ICT. The change in e-administrative services remains a capital problem because it involves a new modeling of the service as well as a new implementation of the system each time there is a change of laws, the presence of specific cases of force majeure (natural disaster). Our approach proposes a generic modeling implemented by a holonic multi agent system (HMAS) to answer the problem of change. Generic modeling and its implementation based on holonic systems make it possible to develop flexible and intelligent systems to deal with the problem of change. The paper presents a case study through which we have dealt with the problem of change in administrative services. The change occurs during a collective move following a natural disaster. The paper ends with a conclusion presenting the perspectives and future work.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| 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".